4711 citations as recorded by crossref.

1. Prediction in HRM research–A gap between rhetoric and reality M. Sarstedt & N. Danks https://doi.org/10.1111/1748-8583.12400
2. Population dynamics and infestation intensity of Diatraea saccharalis (Fabricius) (Lepidoptera: Crambidae) in sugarcane (Saccharum spp.): Adult monitoring as a decision-support tool in pest management É. Carbognin et al. https://doi.org/10.1016/j.cropro.2025.107482
3. Integrated Application of Remote Sensing and GIS in Crop Information System—A Case Study on Aman Rice Production Forecasting Using MODIS-NDVI in Bangladesh B. Faisal et al. https://doi.org/10.3390/agriengineering2020017
4. Support vector machine learning and diffusion-derived structural networks predict amyloid quantity and cognition in adults with Down's syndrome S. Brown et al. https://doi.org/10.1016/j.neurobiolaging.2022.02.013
5. Predicting dissolved organic carbon concentration in a dynamic salt marsh creek via machine learning C. Codden et al. https://doi.org/10.1002/lom3.10406
6. Emergence and early growth of multiple herbicide–resistant and -susceptible late watergrass (Echinochloa phyllopogon) W. Brim-DeForest et al. https://doi.org/10.1017/wet.2021.86
7. Irrigation-Intensive Groundwater Modeling of Complex Aquifer Systems Through Integration of Big Geological Data H. Vahdat-Aboueshagh et al. https://doi.org/10.3389/frwa.2021.623476
8. Three-dimensional inversion of corona structure and simulation of solar wind parameters based on the photospheric magnetic field deduced from the Global Oscillation Network Group X. Zhang et al. https://doi.org/10.3389/fspas.2023.1234391
9. Robust Data Assimilation in River Flow and Stage Estimation Based on Multiple Imputation Particle Filter Z. Ismail & N. Jalaludin https://doi.org/10.1109/ACCESS.2019.2949616
10. A robust objective function for calibration of groundwater models in light of deficiencies of model structure and observations R. Schneider et al. https://doi.org/10.1016/j.jhydrol.2022.128339
11. A deep recurrent neural network approach to inflation forecasting in Nigeria: Evaluating the impact of feature selection methods D. Bartholomew et al. https://doi.org/10.1016/j.fraope.2025.100443
12. Evaluation of Evaporation from Water Reservoirs in Local Conditions at Czech Republic E. Melišová et al. https://doi.org/10.3390/hydrology8040153
13. Short-Term Electricity Load Forecasting Using Artificial Intelligence (Artificial Neural Networks) Method and Meteorological Data for Sivas-Central 1st Organized Industrial Zone S. Keklikci & Y. Torun https://doi.org/10.66248/cumfad.1670257
14. Spatial distribution of lichen communities and air pollution mapping in a tropical city: Medellín, Colombia M. Correa-Ochoa et al. https://doi.org/10.15517/rbt.v69i3.46934
15. Controlling gear selectivity or fishing effort: Which management strategy is more effective for the mixed fisheries? J. Qiao et al. https://doi.org/10.1016/j.ecolmodel.2026.111531
16. Satellite-based estimation of PM2.5 chemical composition under sparse observations in Seoul metropolitan area S. Na et al. https://doi.org/10.1016/j.atmosenv.2026.122402
17. Leakage Signal Denoising of Water Supply Pipelines Based on the Gray Wolf Optimization Algorithm D. Wen et al. https://doi.org/10.1061/JPSEA2.PSENG-2353
18. A New Sphalerite Thermometer Based on Machine Learning with Trace Element Geochemistry H. Zhao et al. https://doi.org/10.1007/s11053-024-10408-3
19. Enhancing the accuracy of rebound test to predict rock UCS: reliability analysis and a novel wave impedance-based approach S. Piao et al. https://doi.org/10.1007/s10064-025-04128-y
20. Qcycle: A Field-Robust Metric for LiFePO4 Battery Degradation Monitoring in Sahelian Solar Irrigation Systems A. Keïta et al. https://doi.org/10.20900/jsr20260067
21. Resolution verification sensing device for a stereo digital image correlation system based on dual-frequency laser interference C. Ma et al. https://doi.org/10.1364/AO.58.009677
22. A dual-stage advanced deep learning algorithm for long-term and long-sequence prediction for multivariate financial time series . Preeti et al. https://doi.org/10.1016/j.asoc.2022.109317
23. Ionosonde total electron content evaluation using International Global Navigation Satellite System Service data T. Klipp et al. https://doi.org/10.5194/angeo-38-347-2020
24. Prediction bands for solar energy: New short-term time series forecasting techniques M. Fliess et al. https://doi.org/10.1016/j.solener.2018.03.049
25. Machine Learning-Based DTCO Log Imputation and Lithology Classification under a Simulated MNAR Missingness Mechanism: A Browse Basin Case Study S. Garini et al. https://doi.org/10.1016/j.rineng.2026.113603
26. Fiberglass-Reinforced Polyester Composites Fatigue Prediction Using Novel Data-Intelligence Model J. Li et al. https://doi.org/10.1007/s13369-018-3508-4
27. Reference evapotranspiration prediction using hybridized fuzzy model with firefly algorithm: Regional case study in Burkina Faso H. Tao et al. https://doi.org/10.1016/j.agwat.2018.06.018
28. Rivages Normands 2100: transdisciplinary co-constructed knowledge for land-use adaptation to groundwater rise along Normandy coastline M. Le Mesnil et al. https://doi.org/10.1007/s11625-026-01896-8
29. Cross-domain neural alignment (CDNA): A deep supervised domain adaptation in human activity recognition using device-free sensing M. Hassan et al. https://doi.org/10.1007/s11042-026-21270-1
30. Improving the accuracy of digital soil mapping using remote sensing and topography covariates in the Central Dry Zone of Myanmar A. Win et al. https://doi.org/10.1016/j.geodrs.2025.e01001
31. Probabilistic safety risk assessment in large-diameter tunnel construction using an interactive and explainable tree-based pipeline optimization method P. Lin et al. https://doi.org/10.1016/j.asoc.2023.110376
32. Parabolic Modeling Forecasts of Space and Time European Hydropower Production C. Lincaru et al. https://doi.org/10.3390/pr12061098
33. Grape Yield Prediction Models: Approaching Different Machine Learning Algorithms C. Andrade et al. https://doi.org/10.3390/horticulturae9121294
34. Risk mapping of wildlife–vehicle collisions across the state of Montana, USA: a machine-learning approach for imbalanced data along rural roads M. Bell et al. https://doi.org/10.1093/tse/tdad043
35. An empirical analysis of explainable artificial intelligence tool for solar radiation prediction C. Santona et al. https://doi.org/10.1007/s44288-026-00554-x
36. Probabilistic performance estimators for computational chemistry methods: The empirical cumulative distribution function of absolute errors P. Pernot & A. Savin https://doi.org/10.1063/1.5016248
37. Application of artificial neural network model in predicting profitability of Indian banks Z. Marak et al. https://doi.org/10.3233/KES-220020
38. Evaluating crisis perturbations on urban mobility using adaptive reinforcement learning C. Fan et al. https://doi.org/10.1016/j.scs.2021.103367
39. Hydraulic conductivity determination by infiltration models in unsaturated soils overlying shallow groundwater regimes D. Jabbar et al. https://doi.org/10.1007/s12517-021-08273-y
40. Concrete Compressive Strength Prediction Using Combined Non-Destructive Methods: A Calibration Procedure Using Preexisting Conversion Models Based on Gaussian Process Regression G. Angiulli et al. https://doi.org/10.3390/jcs8080300
41. Evaluation of long-term degree-days estimated with several methods for corn in Nebraska, USA J. Richmond et al. https://doi.org/10.1007/s00704-021-03885-6
42. A course recommendation model for students based on learning outcome V. Nguyen et al. https://doi.org/10.1007/s10639-021-10524-0
43. Testing kinematic models for low-angle normal fault genesis: Cañada David detachment, Baja California, Mexico M. Balbuena-Salomón et al. https://doi.org/10.1016/j.jsames.2026.106302
44. Predicting air quality using random forest: A case study in Amman-Zarqa F. Alzu’bi et al. https://doi.org/10.1016/j.ejrs.2024.07.004
45. A Deep Learning Approach Replacing the Finite Difference Method for In Situ Stress Prediction W. Gao et al. https://doi.org/10.1109/ACCESS.2020.2977880
46. Characterising the hydrological regime of an ungauged temporary river system: a case study E. D’Ambrosio et al. https://doi.org/10.1007/s11356-016-7169-0
47. CFD-Modeling of the Airfoil of the Blades of a Wind Power Plant with a Vertical Axis in the Ansys Fluent System G. Uzakov et al. https://doi.org/10.21122/1029-7448-2024-67-2-97-114
48. Machine learning estimation of reference evapotranspiration using MODIS-Derived and limited ground variables across Moroccan agro-climatic zones Z. Belarbi & Y. El Younoussi https://doi.org/10.1007/s00704-026-06193-z
49. A hybrid statistical–machine learning framework for evaluating geomagnetic storm effects on MisrSat2 satellite power subsystems M. Mostafa et al. https://doi.org/10.1038/s41598-025-22604-z
50. Implementation of IoT Framework with Data Analysis Using Deep Learning Methods for Occupancy Prediction in a Building E. Hitimana et al. https://doi.org/10.3390/fi13030067
51. Transient pressure wave signal feature extraction for well leakage detection Y. Zhang et al. https://doi.org/10.1063/5.0266723
52. Physically constrained retrieval of intrinsic complex permeability in flaky carbonyl iron/polyurethane composites for microwave absorption J. Li et al. https://doi.org/10.1016/j.jallcom.2026.190938
53. Solar Irradiance Variability: Modeling the Measurements J. Lean et al. https://doi.org/10.1029/2019EA000645
54. Performance of multi-model ensembles for the simulation of temperature variability over Ontario, Canada A. Samouly et al. https://doi.org/10.1007/s12665-018-7701-2
55. Improving subpixel impervious surface estimation based on point of interest (POI) data J. Wang et al. https://doi.org/10.1016/j.jag.2025.104538
56. Estimation of Cold Stress, Plant Age, and Number of Leaves in Watermelon Plants Using Image Analysis S. Nabwire et al. https://doi.org/10.3389/fpls.2022.847225
57. Product Design Time Forecasting by Kernel-Based Regression with Gaussian Distribution Weights Z. Shang & H. Yan https://doi.org/10.3390/e18060231
58. A comparative analysis of similarity measures akin to the Jaccard index in collaborative recommendations: empirical and theoretical perspective V. Verma & R. Aggarwal https://doi.org/10.1007/s13278-020-00660-9
59. Modelling of ocean currents and distribution of total suspended solids in Citarum River estuary A. Namara et al. https://doi.org/10.1051/bioconf/202410603004
60. Phase Transformation Temperature Prediction in Steels via Machine Learning Y. Zhang et al. https://doi.org/10.3390/ma17051117
61. Probabilistic Analysis of Slope Using Bishop Method of Slices with the Help of Subset Simulation Subsequently Aided with Hybrid Machine Learning Paradigm F. Ahmad et al. https://doi.org/10.1007/s40098-023-00796-3
62. Modeling sediment transport and salt stratification in river estuaries: a case study of the Magdalena River, Colombia F. Torres-Bejarano et al. https://doi.org/10.1016/j.catena.2025.109589
63. Reaeration Coefficient Empirical Equation Selection for Water Quality Modeling in Surface Waterbodies: An Integrated Numerical-Modeling-Based Technique with Field Case Study B. Al-Saadi & H. Al-Zubaidi https://doi.org/10.3390/limnolrev25020015
64. Enhanced performance Gaussian process regression for probabilistic short-term solar output forecast F. Najibi et al. https://doi.org/10.1016/j.ijepes.2021.106916
65. Use of modern algorithms for multi-parameter optimization and intelligent modelling of sustainable battery performance A. Afzal et al. https://doi.org/10.1016/j.est.2023.108910
66. An expressway traffic congestion measurement under the influence of service areas L. Liao et al. https://doi.org/10.1371/journal.pone.0279966
67. A Comprehensive Review on High-Fidelity and Metamodel-Based Optimization of Composite Laminates K. Kalita et al. https://doi.org/10.1007/s11831-021-09699-z
68. Sustainable Modeling of the Urban Air Quality in Abu Dhabi Using Machine Learning and Open-Source Satellite Data M. Iruj et al. https://doi.org/10.69709/SusProc.2025.120032
69. Simultaneous Color Restoration and Depth Estimation in Light Field Imaging Y. Li et al. https://doi.org/10.1109/ACCESS.2022.3172343
70. VERTICAL ACCURACY ASSESSMENT OF THE PROCESSED SRTM DATA FOR THE BRAZILIAN TERRITORY A. Orlandi et al. https://doi.org/10.1590/s1982-21702019000400021
71. Computing spiral microwave heating by transformation optics Y. Wu et al. https://doi.org/10.1016/j.csite.2024.104843
72. Long-term evaluation of commercial air quality sensors: an overview from the QUANT (Quantification of Utility of Atmospheric Network Technologies) study S. Diez et al. https://doi.org/10.5194/amt-17-3809-2024
73. Investigation of Joint Types on the Seismic Performance Prediction of RC Beam-Column Joints Based on Machine Learning Method X. Su & H. Yang https://doi.org/10.1080/13632469.2026.2674950
74. Assessment of Precipitation Simulations in Central Asia by CMIP5 Climate Models Z. Ta et al. https://doi.org/10.3390/w10111516
75. MGPP-DL: deep learning approach for material graph properties prediction O. Abbassi et al. https://doi.org/10.1007/s00894-026-06692-w
76. Climate change effects on marine renewable energy resources and environmental conditions for offshore aquaculture in Europe C. Weiss et al. https://doi.org/10.1093/icesjms/fsaa226
77. Room-level conditional graph neural networks for shear wall layout generation in high-rise buildings H. Leng et al. https://doi.org/10.1016/j.autcon.2026.107189
78. Restoration of missing or low-quality 12-lead ECG signals using ensemble deep-learning model with optimal combination H. Yoo et al. https://doi.org/10.1016/j.bspc.2023.104690
79. BAR-based hybrid deep learning framework for bid-rigging detection: reflecting the characteristics of the Korean procurement market E. Lee et al. https://doi.org/10.1016/j.eswa.2026.134047
80. Calibração do modelo de consumo de combustível do simulador AIMSUN com dados coletados via OBD A. Marinho et al. https://doi.org/10.14295/transportes.v26i2.1393
81. Multi-target QSTR modeling for simultaneous prediction of multiple toxicity endpoints of nano-metal oxides N. Basant & S. Gupta https://doi.org/10.1080/17435390.2017.1302612
82. Synergizing low-carbon transportation and heat adaptation: Identifying suitable routes and integrating mitigation and adaptation infrastructure B. He & X. Chen https://doi.org/10.1016/j.buildenv.2024.112448
83. Análisis de Frecuencias bivariado de Crecientes Anuales mediante enfoque práctico de las Funciones Cópula D. Campos-Aranda https://doi.org/10.24850/j-tyca-15-02-01
84. 3D superimposition of cone-beam computed tomography and intraoral scan models for forensic identification: Development and validation of a quantitative analysis method D. Manhaes-Caldas et al. https://doi.org/10.1016/j.forsciint.2026.113133
85. Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia S. Ghimire et al. https://doi.org/10.1016/j.engappai.2022.104860
86. Improved Drought Characteristics in the Pearl River Basin Based on Reconstructed GRACE Solution with Enhanced Temporal Resolution L. Wang et al. https://doi.org/10.3390/rs15194849
87. Settlements extraction and spatiotemporal analysis with SAM and random forest from high-resolution remote sensing M. Liu et al. https://doi.org/10.1016/j.agrcom.2026.100121
88. Exploring Time-Series Deep Learning Models for Ship Fuel Consumption Prediction X. Chen et al. https://doi.org/10.3390/jmse13112102
89. Synthetic Data-Guided Symmetric Neural Network Approximation in Banach Spaces G. Anastassiou et al. https://doi.org/10.3390/axioms15080623
90. Digital mapping of cultivated land soil organic matter in hill-mountain and plain regions H. Xie et al. https://doi.org/10.1007/s11368-023-03633-5
91. Impact of focused wave groups on pier structures: a case study of severe breaking waves at Pont del Petroli during storm Gloria C. Altomare et al. https://doi.org/10.3389/fbuil.2024.1372906
92. Thermal pleasure–based spacing of mist–shade umbrellas in hot–humid outdoor walkways using an extended JOS-3 model D. Lu et al. https://doi.org/10.1016/j.enbuild.2026.117853
93. Missing value imputation for the analysis of incomplete traffic accident data R. Deb & A. Liew https://doi.org/10.1016/j.ins.2016.01.018
94. The impact of the spatiotemporal structure of rainfall on flood response over a piedmont urban basin: An approach coupling machine learning and hydrologic modeling S. Xu et al. https://doi.org/10.1016/j.jhydrol.2025.133160
95. Scaled sequential threshold least-squares (S2TLS) algorithm for sparse regression modeling and flight load prediction S. Zhu & Y. Wang https://doi.org/10.1016/j.ast.2018.12.038
96. Effectiveness of large language models in automated evaluation of argumentative essays: finetuning vs. zero-shot prompting Q. Wang & J. Gayed https://doi.org/10.1080/09588221.2024.2371395
97. Nature, economy and mental health: Predictive insights from historical language patterns M. Richardson https://doi.org/10.1016/j.jenvp.2026.103078
98. Predicting 5-Year EDSS in Multiple Sclerosis with LSTM Networks: A Deep Learning Approach to Disease Progression İ. Kırkbir et al. https://doi.org/10.1016/j.jocn.2025.111218
99. Quantifying and evaluating the impacts of cooperation in transboundary river basins on the Water-Energy-Food nexus: The Blue Nile Basin M. Basheer et al. https://doi.org/10.1016/j.scitotenv.2018.02.249
100. Evaluation of pressure fluctuations coefficient along the USBR Type II stilling basin using experimental results and AI models S. Mousavi et al. https://doi.org/10.1080/09715010.2020.1743208
101. Assessing current and future spatiotemporal precipitation variability and trends over Uganda, East Africa, based on CHIRPS and regional climate model datasets H. Ngoma et al. https://doi.org/10.1007/s00703-021-00784-3
102. Short-term electricity demand forecasting using machine learning methods enriched with ground-based climate and ECMWF Reanalysis atmospheric predictors in southeast Queensland, Australia M. AL-Musaylh et al. https://doi.org/10.1016/j.rser.2019.109293
103. Air quality assessment using geospatial technique and artificial neural network (ANN) analysis for an urban city, Uttar Pradesh (India) A. Dixit et al. https://doi.org/10.1680/jenes.25.00019
104. Prediction of Water Quality Parameters in the Paraopeba River Basin Using Remote Sensing Products and Machine Learning R. Dias et al. https://doi.org/10.3390/s26010018
105. Enhanced spatial precipitation maps by integrating XGBoost machine learning, terrain indices, and optimal interpolation P. Ahmed et al. https://doi.org/10.1007/s00704-026-06177-z
106. Physics-guided residual learning for predicting aerodynamic characteristics of 3D wing under diverse operating conditions S. Kim et al. https://doi.org/10.1016/j.ast.2026.112606
107. Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques . Durr-e-Nayab et al. https://doi.org/10.1109/ACCESS.2021.3067816
108. Interpretable Data-Driven Ozone Prediction Using Statistical Diagnostics, XGBoost, SHAP and Temporal Fusion Transformers B. Hu et al. https://doi.org/10.3390/su18021009
109. Applications and interpretations of different machine learning models in runoff and sediment discharge simulations J. Miao et al. https://doi.org/10.1016/j.catena.2024.107848
110. Study of heat wave events by the thermophysiological comfort indexes in Khulna City, Bangladesh, during pre-monsoon and monsoon seasons F. Rahman et al. https://doi.org/10.1016/j.cacint.2025.100275
111. Functional evaluation of linearized Langmuir equations to characterize cadmium sorption and transport in selected calcareous soils H. Khodaverdiloo et al. https://doi.org/10.1007/s12517-020-06444-x
112. Yield Estimation of Winter Wheat in Pre-harvest Season by Satellite Imagery Based Regression Models E. UNAL et al. https://doi.org/10.46592/turkager.2020.v01i02.013
113. Customer Satisfaction in City Delivery Systems and Its Implications for Delivery Efficiency and Environmental Impacts: A Machine Learning Analysis A. Medić et al. https://doi.org/10.3390/su18157786
114. An Evaluation of Mathematical Modeling of Ethanol Fermentation with Immobilized Saccharomyces cerevisiae in the Presence of Different Inhibitors S. Ünsal et al. https://doi.org/10.3390/pr13030656
115. Using a Multi-Output Neural Network Model to Standardize Heterogeneous Fisheries Data Z. Xu et al. https://doi.org/10.1007/s11802-025-6136-0
116. Machine Learning-Based Molecular Dynamics Studies on Predicting Thermophysical Properties of Ethanol–Octane Blends A. Shateri et al. https://doi.org/10.1021/acs.energyfuels.4c05653
117. Enhancing Shelf Life Prediction of Fresh Pizza with Regression Models and Low Cost Sensors P. Wunderlich et al. https://doi.org/10.3390/foods12061347
118. A novel fiber-optic measurement system for the evaluation of performances of neonatal pulmonary ventilators L. Battista et al. https://doi.org/10.1088/0957-0233/27/2/025704
119. Using Multilevel Models to Compare Performance Prediction and Characterization Abilities Between Power-Law and Critical-Speed Models in Middle- and Long-Distance Running M. Walt et al. https://doi.org/10.1123/ijspp.2024-0330
120. Predictive Model for Growth of Bacillus cereus at Temperatures Applicable to Cooling of Cooked Pasta V. Juneja et al. https://doi.org/10.1111/1750-3841.14448
121. Multimodal Optimization: An Effective Framework for Model Calibration M. Chica & J. Barranquero https://doi.org/10.2139/ssrn.2828069
122. An autonomic prediction suite for cloud resource provisioning A. Nikravesh et al. https://doi.org/10.1186/s13677-017-0073-4
123. Drought prediction in Jilin Province based on deep learning and spatio-temporal sequence modeling Z. Hou et al. https://doi.org/10.1016/j.jhydrol.2024.131891
124. Ultra-Short-Term Solar Power Prediction Using Sky Image Sequences by a Residual Vision Reformer R. Rastgoo et al. https://doi.org/10.1109/TSTE.2025.3575520
125. DeepScaling: Autoscaling Microservices With Stable CPU Utilization for Large Scale Production Cloud Systems Z. Wang et al. https://doi.org/10.1109/TNET.2024.3400953
126. Development of a hybrid Digital Twin for the dispersion of transient CO2 clouds accompanying accidental pipeline leaks P. Bielka et al. https://doi.org/10.1016/j.ijggc.2025.104528
127. Modeling wetland aboveground biomass in the Poyang Lake National Nature Reserve using machine learning algorithms and Landsat-8 imagery R. Wan et al. https://doi.org/10.1117/1.JRS.12.046029
128. Comparison of feature learning methods for non-invasive interstitial glucose prediction using wearable sensors in healthy cohorts: a pilot study X. Huang et al. https://doi.org/10.1016/j.imed.2024.05.002
129. Body Boundary Measurement Using Multiple Line Lasers for a Focused Microwave Thermotherapy System: A Proof-of-Concept Study J. Jeong & S. Son https://doi.org/10.3390/s23177438
130. Advanced Data Analytics and Machine Learning for Geospatial Interpolation, Anomaly Detection, Background Prediction and Emergency Evacuation Routing in Real-Time Radiation Monitoring System M. Omio et al. https://doi.org/10.1097/HP.0000000000002149
131. Automated accuracy assessment for ridge and valley polylines using high-resolution digital elevation models P. Dong https://doi.org/10.1130/GES01477.1
132. A systematic review on predicting PV system parameters using machine learning M. Jobayer et al. https://doi.org/10.1016/j.heliyon.2023.e16815
133. Customised Selection of the Haptic Design in C-Loop Intraocular Lenses Based on Deep Learning I. Cabeza-Gil et al. https://doi.org/10.1007/s10439-020-02636-4
134. Analyzing the spatiotemporal distribution of climate extremes under the CMIP6 climate model in the upper Blue Nile Basin, Ethiopia F. Enyew et al. https://doi.org/10.1007/s11069-026-07998-x
135. A novel deep learning algorithm for Phaeocystis counting and density estimation based on feature reconstruction and multispectral generator Y. Si et al. https://doi.org/10.1016/j.neucom.2024.128674
136. A Correction Method for Heat Wave Distortion in Digital Image Correlation Measurements Based on Background-Oriented Schlieren C. Ma et al. https://doi.org/10.3390/app9183851
137. Simulation Based Evaluation of Time Series for Syndromic Surveillance of Cattle in Switzerland C. Faverjon et al. https://doi.org/10.3389/fvets.2019.00389
138. Hybrid Deep Learning Model Integrating Attention Mechanism for the Accurate Prediction and Forecasting of the Cryptocurrency Market G. Saqware & I. B https://doi.org/10.1007/s43069-024-00302-2
139. Modelling the Thermal Effects on Structural Components of Composite Slabs under Fire Conditions C. Balsa et al. https://doi.org/10.3390/computation10060094
140. Factors influencing the effectiveness of machine learning algorithms in predicting raw wastewater characteristics: An analysis based on weekly field data H. Khoshvaght et al. https://doi.org/10.1016/j.jwpe.2025.108702
141. An interpretable approach using hybrid graph networks and explainable AI for intelligent diagnosis recommendations in chronic disease care M. Huang et al. https://doi.org/10.1016/j.bspc.2023.105913
142. Effect of time-series length on drought index results in semi-arid regions S. AL-Kalo & O. Mahmood Agha https://doi.org/10.1016/j.pce.2026.104846
143. Smart Water Quality Monitoring with IoT Wireless Sensor Networks Y. Singh & T. Walingo https://doi.org/10.3390/s24092871
144. Multi-source data-driven estimation of urban net primary productivity: A case study of Wuhan J. Chen et al. https://doi.org/10.1016/j.jag.2023.103638
145. Relationship of soil moisture characteristic curve and mechanical properties in Entisols and Inceptisols of Iran E. Ebrahimi et al. https://doi.org/10.1016/j.geodrs.2021.e00434
146. A multi-attention Uformer for low-dose CT image denoising H. Yan et al. https://doi.org/10.1007/s11760-023-02853-z
147. Carbon emission prediction of 275 cities in China considering artificial intelligence effects and feature interaction: A heterogeneous deep learning modeling framework G. Zhang et al. https://doi.org/10.1016/j.scs.2024.105776
148. Gap-filling missing data in time series using the correlation matrix method of multiple time series in Asadabad Plain, Iran H. Nozari et al. https://doi.org/10.1007/s40899-023-00977-1
149. Spatiotemporal Bayesian modeling of the risk of congenital syphilis in São Paulo, SP, Brazil R. Cruz et al. https://doi.org/10.1016/j.sste.2024.100651
150. An improved approach for solving the adaptive coefficient in the aPMV (adaptive predictive mean vote) index S. Zhang et al. https://doi.org/10.1016/j.buildenv.2024.111481
151. Enhancing spatial modeling and risk mapping of six air pollutants using synthetic data integration with convolutional neural networks A. Bashardoost et al. https://doi.org/10.3389/fenvs.2024.1399339
152. Machine Learning-Based Mapping of Daily Methane Concentration in Rice Paddies Using Meteorological Data and Satellite Images: A Case of South Korea J. Jang et al. https://doi.org/10.7780/kjrs.2024.40.6.1.18
153. Spatio‐temporal evaluation of gridded precipitation products for the high‐altitude Indus basin Z. Dahri et al. https://doi.org/10.1002/joc.7073
154. Prediction of evening fatigue severity in outpatients receiving chemotherapy: less may be more K. Kober et al. https://doi.org/10.1080/21641846.2021.1885119
155. Dilute acid and alkaline pretreatment of spent tea leaves to determine the potential of carbon sources M. Germec et al. https://doi.org/10.1007/s13399-018-0301-2
156. Modeling risk perception using independent and social learning: application to individuals with autism spectrum disorder T. Wadhera & D. Kakkar https://doi.org/10.1080/0022250X.2020.1774877
157. Comparison of machine learning methods for dry biomass estimation based on green logging residues chips R. De la Fuente et al. https://doi.org/10.1080/14942119.2021.1892415
158. UCMR-Net: Text-Anchored Residual Fusion with Adaptive Residual Weighting for Multimodal Sentiment Intensity Prediction D. Tang et al. https://doi.org/10.3390/app16147142
159. Efficient Reduced-Order modeling for steam turbine rotors using TCN-enhanced SVD X. Cai et al. https://doi.org/10.1016/j.applthermaleng.2025.126168
160. Data Mining, Weka Decision Trees Z. Duran et al. https://doi.org/10.56038/oprd.v3i1.376
161. An Extended Flood Characteristic Simulation Considering Natural Dependency Structures M. Öttl et al. https://doi.org/10.3390/hydrology10120233
162. Perceptual Quality Assessment of Real-World Noise in Ultra-High-Definition Images B. Zheng et al. https://doi.org/10.1109/TIP.2026.3739609
163. Air temperature trend analysis for the Cananéia–Iguape Coastal System (São Paulo State, Brazil), 1981–2022, using reanalysis products evaluated against surface observations J. Baratto et al. https://doi.org/10.1016/j.dynatmoce.2026.101676
164. Monitoring leaf area index of the sown mixture pasture through UAV multispectral image and texture characteristics X. Wang et al. https://doi.org/10.1016/j.compag.2023.108333
165. Data-driven refined modeling and simulation of hydro-turbine prototype performance via 3D affine transformation correction M. Yuanyuan et al. https://doi.org/10.1016/j.seta.2026.105409
166. A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project P. Barmpas et al. https://doi.org/10.1007/s13755-022-00171-1
167. Khám phá các yếu tố ảnh hưởng đến sự hài lòng của sinh viên đối với hoạt động giảng dạy của giảng viên thông qua các mô hình học máy: nghiên cứu tại trường Đại học Thương mại L. Nguyen Thi & H. Doan Huy https://doi.org/10.54404/JTS.2025.199V.06
168. Machine Learning-Augmented Tidal Signature Extraction from GNSS Interferometric Reflectometry (GNSS-IR) Observations I. Zulkurnain https://doi.org/10.52939/ijg.v22i1.4725
169. CoGait WalkAssist: Design and Evaluation of a Motor-Free Lower-Limb Rehabilitation Robot for Natural Gait Training on Treadmills M. Bakhtiari et al. https://doi.org/10.1109/ACCESS.2025.3610525
170. Artificial intelligence-based ensemble learning for robust prediction of hydrogen in supercritical water gasification using experimental data Y. Ayub et al. https://doi.org/10.1016/j.ijhydene.2026.154285
171. Prediction of Stress-strain Behavior for Polyurethane Elastomers Based on Machine Learning L. Zhou et al. https://doi.org/10.1007/s10118-026-3606-9
172. Leaf area index estimation using 3D modeling and end-to-end deep regression Y. Deng et al. https://doi.org/10.1016/j.atech.2026.102379
173. An Innovative Hybrid Model of ARIMA and Random Forest for Predicting MOOC Learning Outcomes P. Su & C. Su https://doi.org/10.70003/160792642026092705008
174. Optimizing sheep growth curves using a meta-heuristic algorithm M. Benvenga et al. https://doi.org/10.1007/s11250-024-04188-4
175. Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems X. Wen et al. https://doi.org/10.1016/j.jhydrol.2018.12.060
176. Evaluation of tree-based ensemble algorithms for predicting the big five personality traits based on social media photos: Evidence from an Iranian sample M. Khorrami et al. https://doi.org/10.1016/j.paid.2021.111479
177. Three-dimensional cohesive finite element simulations coupled with machine learning to predict mechanical properties of polymer-bonded explosives D. Lu et al. https://doi.org/10.1016/j.compscitech.2024.110947
178. Predicting outcomes of smoking cessation interventions in novel scenarios using ontology-informed, interpretable machine learning J. Hastings et al. https://doi.org/10.12688/wellcomeopenres.20012.2
179. Evaluation of statistical models and modern hybrid artificial intelligence in the simulation of precipitation runoff process R. Dehghani et al. https://doi.org/10.1007/s40899-022-00743-9
180. Snowmelt runoff model (SRM) for regulated watersheds with regulation-correction N. Bhagwat et al. https://doi.org/10.1007/s13201-025-02579-y
181. The multi-strategy hybrid forecasting base on SSA-VMD-WST for complex system H. Su et al. https://doi.org/10.1371/journal.pone.0300142
182. Development of a Testing Method for the Accuracy and Precision of GNSS and LiDAR Technology K. Romero et al. https://doi.org/10.3390/agriengineering7090310
183. Developing an Innovative Method for Visual Perception Evaluation in a Physical-Based Virtual Environment F. Abd-Alhamid et al. https://doi.org/10.1016/j.buildenv.2019.106278
184. Identifying impacts of global climate teleconnection patterns on land water storage using machine learning I. Kalu et al. https://doi.org/10.1016/j.ejrh.2023.101346
185. The impact of the automated ball-strike system (ABS) on baseball: A deep learning based counterfactual approach S. Hwang et al. https://doi.org/10.1177/17543371251395162
186. Performance of Deep Feed-Forward Neural Network Algorithm Based on Content-Based Filtering Approach F. Maulana & E. Setiawan https://doi.org/10.29407/intensif.v8i2.22904
187. An automated machine learning approach for earthquake casualty rate and economic loss prediction W. Chen & L. Zhang https://doi.org/10.1016/j.ress.2022.108645
188. Enhanced hydrological drought prediction in the Gediz Basin: integrating meteorological drought via hybrid wavelet-machine learning-random oversampling models using E. Taylan https://doi.org/10.2166/wcc.2024.324
189. Bridging gaps in sparse groundwater data: classical, ensemble, and deep learning approaches for single- and multi-well imputation H. Sejine et al. https://doi.org/10.3389/frwa.2025.1726853
190. Data-driven decision support for inventory planning: A Lean, Agile, Resilient, and Green (LARG) perspective G. Vidal et al. https://doi.org/10.1016/j.compind.2026.104537
191. Systematic Error Analysis and Calibration of 2-m Temperature for the NCEP GEFS Reforecast of the Subseasonal Experiment (SubX) Project H. Guan et al. https://doi.org/10.1175/WAF-D-18-0100.1
192. A comprehensive guideline for hybrid modeling of engineered microbial processes Z. Cheng et al. https://doi.org/10.1016/j.watres.2025.124559
193. A Comparative Study of Student Performance Prediction using Pre-Course Data B. Alharbi et al. https://doi.org/10.14201/ADCAIJ20211014961
194. Effects of waste-based pyrolysis as heating source: Meta-analyze of char yield and machine learning analysis Z. Huang et al. https://doi.org/10.1016/j.fuel.2022.123578
195. Modelling the Survival of Acid-Adapted and Nonadapted Escherichia coli O157:H7 in Burkina: A Western African Traditional Fermented Milk Product L. Donkor et al. https://doi.org/10.1155/2023/1011319
196. Enhancing the Accuracy of Thermal Model Calibration: Integrating Zone Air and Surface Temperatures, Convection Coefficients, and Solar and Thermal Absorptivity M. Demarchi et al. https://doi.org/10.1016/j.enbuild.2025.115617
197. A Novel Trigger Mechanism for a Dual-Filter to Improve the State-of-Charge Estimation of Lithium-Ion Batteries C. Yu et al. https://doi.org/10.1115/1.4052993
198. A data-driven workflow for constructing depth-dependent rock-physics templates for the Oligocene D Formation in the Cuu Long Basin, offshore Vietnam L. Nguyen Danh et al. https://doi.org/10.15625/2615-9783/25119
199. A novel artificial intelligence approach for regolith geochemical grade prediction using multivariate adaptive regression splines F. Majeed et al. https://doi.org/10.1016/j.geogeo.2022.100038
200. An experimental study and regression analysis to estimate the reduction time of mill scale by coal S. Das et al. https://doi.org/10.1016/j.matpr.2020.01.160
201. Spatio-Temporal Gap Filling of Sentinel-2 NDI45 Data Using a Variance-Weighted Kalman Filter and LSTM Ensemble I. Haidu et al. https://doi.org/10.3390/s25175299
202. Short-term wind power forecasting using KNN, SVR, and linear regression with high-resolution SCADA data S. Çelebi et al. https://doi.org/10.1177/0309524X261417206
203. Integrating Target Variable Selection Into Environmental Machine Learning for Surface Water Pollution Management C. Chang & Z. He https://doi.org/10.1002/wer.70588
204. Modeling the reactivities of hydroxyl radical and ozone towards atmospheric organic chemicals using quantitative structure-reactivity relationship approaches S. Gupta et al. https://doi.org/10.1007/s11356-016-6527-2
205. Compact device modelling of interface trap charges with quantum capacitance in MoS2-based field-effect transistors C. Leong et al. https://doi.org/10.1088/1361-6641/ab74f2
206. Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models O. Kisi et al. https://doi.org/10.1080/02626667.2019.1632460
207. Using differences in abiotic factors between seed origin and common garden sites to predict performance of Pacific madrone (Arbutus menziesii Pursh) R. Kamakura et al. https://doi.org/10.1016/j.foreco.2021.119487
208. CNN-based severity prediction of neurodegenerative diseases using gait data Ç. Berke Erdaş et al. https://doi.org/10.1177/20552076221075147
209. Extreme Feature Regions Detection and Accurate Quality Assessment for Point-Cloud 3D Reconstruction Y. Rao et al. https://doi.org/10.1109/ACCESS.2019.2898731
210. Evaluation of Regional Climate Models (RCMs) Performance in Simulating Seasonal Precipitation over Mountainous Central Pindus (Greece) S. Stefanidis et al. https://doi.org/10.3390/w12102750
211. Comparative Analysis of Time Series Method for Forecasting the Call Arrival of Call Center K. Ryu & W. Kim https://doi.org/10.14801/jkiit.2018.16.8.83
212. The reverse interpolation and its application in the numerical solutions of Fredholm integral equations of the second kind S. Mirzaei & M. Amirfakhrian https://doi.org/10.1007/s40314-019-0950-1
213. Cultivation of the polychaete worm Sabella spallanzanii (Gmelin, 1791) in a novel multi-species IMTA (integrated multi-trophic aquaculture) system in the Mediterranean Sea D. Arduini et al. https://doi.org/10.1016/j.aquaculture.2025.743248
214. Reconstruction of Solar Extreme-ultraviolet Irradiance Using Ca II K Images and SOHO/SEM Data with Bayesian Deep Learning and Uncertainty Quantification H. Jiang et al. https://doi.org/10.3847/1538-4365/adfa0d
215. Interpolation of the gaps in current maps generated by high-frequency radar D. Saha et al. https://doi.org/10.1080/01431161.2016.1230281
216. The development of dissolved oxygen forecast model using hybrid machine learning algorithm with hydro-meteorological variables A. Ahmed et al. https://doi.org/10.1007/s11356-022-22601-z
217. A deep learning approach predicts O3 increase and PM2.5 declines under high emission scenario across the Northern China urban agglomeration G. Zhang et al. https://doi.org/10.1016/j.uclim.2025.102752
218. Joint Action of Wind and Temperature for a Long-Span Cable-Stayed Bridge in Plateau Canyon Regions Using SHM Data and Copula-Based Probabilistic Modeling J. Liu et al. https://doi.org/10.3390/buildings16050916
219. Gene expression models based on a reference laboratory strain are poor predictors of Mycobacterium tuberculosis complex transcriptional diversity Á. Chiner-Oms et al. https://doi.org/10.1038/s41598-018-22237-5
220. Periderm coverages on five species of long-lived columnar cactus species of central Mexico L. Evans https://doi.org/10.1016/j.flora.2020.151701
221. Speed Management Strategy: Designing an IoT-Based Electric Vehicle Speed Control Monitoring System G. Antoine et al. https://doi.org/10.3390/s21196670
222. New indices to quantify patterns of relative errors produced by spatial interpolation models – A comparative study by modelling soil properties U. Bronowicka-Mielniczuk & J. Mielniczuk https://doi.org/10.1016/j.ecolind.2023.110551
223. Neural emulator based on physical fields for accelerating the simulation of surface chlorophyll in an Earth System Model B. Wu et al. https://doi.org/10.1016/j.ocemod.2024.102491
224. The impact of sampling depths on quantification of soil organic carbon stock in mangrove environments I. Cooray et al. https://doi.org/10.1016/j.catena.2024.108398
225. Spatiotemporal drought analysis and future risk assessment using multi-index remote sensing approach and hybrid trend-based prediction modeling A. Polat et al. https://doi.org/10.1007/s10661-025-14895-6
226. Hybrid APSO-Bayesian optimized triple-kernel SVR models for QSAR and rational design of 1H-pyrrolo[2,3-c]pyridine-based LSD1 Inhibitors R. Tian et al. https://doi.org/10.1007/s11030-026-11560-z
227. Does Selecting Covariates Using Factor Analysis in Mapping Algorithms Improve Predictive Accuracy? A Case of Predicting EQ-5D-5L and SF-6D Utilities from the Women’s Health Questionnaire B. Kaambwa et al. https://doi.org/10.1016/j.jval.2018.01.020
228. Intercomparison of multisource actual evapotranspiration satellite products in Bilate watershed, Ethiopia A. Yimer et al. https://doi.org/10.15446/esrj.v28n2.111726
229. Development of a spectral library (CROPSPECPK) for major crops through spectroscopy modeling and in-situ spectrometer data D. Raza et al. https://doi.org/10.1186/s12870-026-08387-z
230. An explainable artificial intelligence feature selection framework for transparent, trustworthy, and cost-efficient energy forecasting L. Kost et al. https://doi.org/10.1016/j.egyai.2025.100648
231. Stock Prices Forecasting by Using a Novel Hybrid Method Based on the MFO-Optimized GRU Network X. Zhang & G. Liu https://doi.org/10.1007/s40745-025-00616-w
232. Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations E. Kalafatoglu Eyiguler et al. https://doi.org/10.1029/2018SW002033
233. An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction Z. Yaseen et al. https://doi.org/10.1016/j.jhydrol.2018.11.069
234. Forecasting IT security vulnerabilities – An empirical analysis E. Yasasin et al. https://doi.org/10.1016/j.cose.2019.101610
235. Evaluation System of Curved Conveyor Belt Deviation State Based on the ARIMA–LSTM Combined Prediction Model X. Sun et al. https://doi.org/10.3390/machines10111042
236. Analysis of the influence of bathymetry on regular representative and realistic irregular waves generated through the WaveMIMO methodology A. Mocellin et al. https://doi.org/10.5902/2179460X87168
237. Sustainable Sewage Treatment Prediction Using Integrated KAN-LSTM with Multi-Head Attention J. Zheng et al. https://doi.org/10.3390/su17104417
238. A Sequence-Based Hybrid Ensemble Approach for Estimating Trail Pavement Roughness Using Smartphone and Bicycle Data Y. Alatoom et al. https://doi.org/10.3390/infrastructures9100179
239. Uncertainty-aware asynchronous scattered motion interpolation using Gaussian process regression B. Kocev et al. https://doi.org/10.1016/j.compmedimag.2018.12.001
240. Predicting Pyrodinium bahamense occurrence using weather pattern data in Eastern Visayas, Philippines A. Yu et al. https://doi.org/10.1007/s10661-021-09380-9
241. Deep Learning Modelling and Generalisation of Carbonation Depth in Fly Ash Blended Concrete I. Uwanuakwa https://doi.org/10.1007/s13369-020-05093-2
242. Stripe Error Correction for Landsat-7 Using Deep Learning H. Adıyaman et al. https://doi.org/10.1007/s41064-024-00306-x
243. Exploring the Role of Urban Green Spaces in Regulating Thermal Environments: Comparative Insights from Seoul and Busan, South Korea J. Xia et al. https://doi.org/10.3390/f16101515
244. A Novel Approach for Accurate Estimation of Furrow Cross‐Section and Wetted Perimeter Using a Normalized Beta Distribution Function A. Seyedzadeh et al. https://doi.org/10.1002/ird.70099
245. Interpetatle data mining for legume crude protein prediction M. ÇATAL https://doi.org/10.1016/j.indcrop.2026.122664
246. A stacked ensemble artificial neural network algorithm for efficient solar energy prediction S. Ghimire et al. https://doi.org/10.1007/s00500-026-11437-1
247. Graph Based Feature Selection for Reduction of Dimensionality in Next-Generation RNA Sequencing Datasets C. Gakii et al. https://doi.org/10.3390/a15010021
248. Ground water quality assessment and forecasting using attention-based mechanisms S. Sundhar et al. https://doi.org/10.1186/s12302-025-01216-4
249. Process-Driven Cross-Factor Integration of SWAT and Interpretable Machine Learning for Enhancing Riverine Total Nitrogen Prediction X. Xi et al. https://doi.org/10.1021/acsestwater.5c01391
250. Using Context-Guided data Augmentation, lightweight CNN, and proximity detection techniques to improve site safety monitoring under occlusion conditions H. Chen et al. https://doi.org/10.1016/j.ssci.2022.105958
251. CT-TreeFlow: Probabilistic Groundwater-Potential Mapping Using Remote Sensing-Derived Environmental Predictors in Karst Aquifers S. Pourmorad et al. https://doi.org/10.3390/rs18132258
252. Diffraction-Net: a robust single-shot holography for multi-distance lensless imaging H. Luo et al. https://doi.org/10.1364/OE.472658
253. A Nonparametric Approach Trained by Metaheuristic Algorithm for Voltage Regulation in the Electrical Distribution Network Equipped by PV Farm S. Salah et al. https://doi.org/10.1007/s42835-022-01158-4
254. A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers D. Tien Bui et al. https://doi.org/10.3390/su12031063
255. ATOM: AI-Powered Sustainable Resource Management for Serverless Edge Computing Environments M. Golec et al. https://doi.org/10.1109/TSUSC.2023.3348157
256. Global Wildfire Susceptibility Mapping Based on Machine Learning Models A. Shmuel & E. Heifetz https://doi.org/10.3390/f13071050
257. Interaction between Si4+/Al3+ and alkali metal ions governing coal ash fusion behavior Y. Wang et al. https://doi.org/10.1016/j.fuel.2026.139419
258. Process Monitoring of Internal Wall Loss in Hot-Fluid Pipelines Using External Fiber Bragg Grating Thermometry and Residual-Peak Morphology L. Zhu et al. https://doi.org/10.3390/pr14172718
259. Ensemble Machine Learning Techniques for Accurate and Efficient Detection of Botnet Attacks in Connected Computers S. Afrifa et al. https://doi.org/10.3390/eng4010039
260. Custom Methodology to Improve Geospatial Interpolation at Regional Scale with Open-Source Software C. Massarelli et al. https://doi.org/10.3390/knowledge2010005
261. Towards More Reliable Gridded Precipitation Estimates: Gauge-Based Multi-Scale Evaluation and Machine Learning Bias Correction S. Saghiry et al. https://doi.org/10.1007/s41748-025-01000-7
262. Integrating mechanism diagnosis and physics-guided machine learning for wind field simulation and speed correction in complex terrain M. Du et al. https://doi.org/10.1016/j.jastp.2026.106801
263. Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study H. Tanyildizi-Kokkulunk https://doi.org/10.1515/bmt-2024-0620
264. Evaluation of merged multi-sensor ocean-color chlorophyll products in the Northern Persian Gulf M. Moradi https://doi.org/10.1016/j.csr.2021.104415
265. Overview of the Constitutive Model and Numerical Calibration by FEM to Compute Bearing Capacity and Embankment-Core Deformability M. Mesa Lavista et al. https://doi.org/10.15446/ing.investig.v42n1.93712
266. Estimation of leaf area index for winter wheat at early stages based on convolutional neural networks Y. Li et al. https://doi.org/10.1016/j.compag.2021.106480
267. A Quest for Context-Specific Stock Price Prediction: A Comparison Between Time Series, Machine Learning and Deep Learning Models M. Kulkarni et al. https://doi.org/10.1007/s42979-025-03848-y
268. What reveals about depression level? The role of multimodal features at the level of interview questions S. Guohou et al. https://doi.org/10.1016/j.im.2020.103349
269. Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems A. Boukerche et al. https://doi.org/10.1016/j.comnet.2020.107484
270. Performance metrics for the assessment of satellite data products: an ocean color case study B. Seegers et al. https://doi.org/10.1364/OE.26.007404
271. Predicting construction equipment resale price: machine learning model H. Toma et al. https://doi.org/10.1108/ECAM-08-2023-0857
272. Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices J. Piao & S. Kim https://doi.org/10.3390/s17112567
273. An Innovative Deep Learning Futures Price Prediction Method with Fast and Strong Generalization and High-Accuracy Research L. Huo et al. https://doi.org/10.3390/app14135602
274. Spatial assessment of soil quality under different land use and land cover patterns in a micro-catchment of the Central Black Sea Region, Türkiye S. Pacci et al. https://doi.org/10.18393/ejss.1924804
275. Efficient removal of Ni, Al, and As from water using Micrococcus yunnanensis: batch experiments and explainable machine learning A. Uçkun et al. https://doi.org/10.1007/s10532-026-10371-1
276. Remediation of chaos in cognitive Internet of Things sensor network V. Jha & P. Tripathi https://doi.org/10.1016/j.adhoc.2025.103830
277. Computer Vision-Based RULA Assessment: A Comparison With IMU Sensors for Static and Dynamic Occupational Tasks A. Ismiyati et al. https://doi.org/10.1177/10711813261485913
278. Análisis de Frecuencias de Crecientes trivariados con dependencia regional y Funciones Cópula D. Campos Aranda https://doi.org/10.24850/j-tyca-16-1-6
279. A Local Feature Engineering Strategy to Improve Network Anomaly Detection S. Carta et al. https://doi.org/10.3390/fi12100177
280. Urbanity mapping reveals the complexity, diffuseness, diversity, and connectivity of urbanized areas D. Zhaxi et al. https://doi.org/10.1016/j.geosus.2024.03.004
281. Physics-Consistent Monotonic Machine Learning for RMR Prediction from Q-System Parameters Under Duplicate-Aware Validation Y. Zhang et al. https://doi.org/10.1007/s00603-026-05949-3
282. Design and Control Prismatic Triangular Tensegrity Robot With Linearly Actuated Struts A. Ismagambetov et al. https://doi.org/10.1115/1.4070414
283. Review of deep learning-based ground-sky imagery method for intra-hour solar irradiance forecasting: Workflow and perspectives L. Zhang et al. https://doi.org/10.1016/j.rser.2026.117160
284. Forecasting the development of electricity from renewable energy sources in Poland against the background of the European Union countries M. Stanuch & K. Firlej https://doi.org/10.34659/eis.2023.84.1.536
285. A GIS-Driven, Machine Learning-Enhanced Framework for Adaptive Land Bonitation B. Văduva et al. https://doi.org/10.3390/agriculture15161735
286. A Comparative Study of SSA-BPNN, SSA-ENN, and SSA-SVR Models for Predicting the Thickness of an Excavation Damaged Zone around the Roadway in Rock G. Zhao et al. https://doi.org/10.3390/math10081351
287. Numerical Simulation of River-Borne Debris Trajectories and Dispersion Patterns in Lamong Bay, Indonesia H. Muzhofar et al. https://doi.org/10.1088/1755-1315/1628/1/012042
288. Economic costs of the invasive Yellow-legged hornet on honey bees F. Requier et al. https://doi.org/10.1016/j.scitotenv.2023.165576
289. A geometry-based slip prediction model for planetary rovers H. Ma et al. https://doi.org/10.1016/j.compeleceng.2020.106749
290. Application of artificial neural network with backpropagation algorithm for estimating leaf area E. Asriani & . Robika https://doi.org/10.1088/1755-1315/599/1/012046
291. A New Technique for Improving the Precision of Dual-Axis Tetrahedron-Based Sensor With Switching Between PID and ANN Y. Away et al. https://doi.org/10.1109/ACCESS.2023.3305944
292. GSA-cGAN: A Geospatial-Aware Conditional Wasserstein Generative Adversarial Network for Mineral Resources Interpolation H. Han & J. Suh https://doi.org/10.3390/app16020674
293. Capability of GLAS/ICESat Data to Estimate Forest Canopy Height and Volume in Mountainous Forests of Iran M. Pourrahmati et al. https://doi.org/10.1109/JSTARS.2015.2478478
294. Genetic Algorithm-Optimized Neural Network for Efficient Soil Health Assessment: An Engineering Approach for Sustainable Agriculture R. Silva et al. https://doi.org/10.1021/acsestengg.5c01028
295. Seasonal variation of coastal currents and residual currents in the CAT BA – HA long coastal area (VIET NAM): Results of coherens model V. Vinh et al. https://doi.org/10.1016/j.rsma.2024.103874
296. Early Warning of Nerve Agent Release in Large Indoor Environments Based on Encoder-Decoder Coupling Physics-Informed Neural Network S. Sun et al. https://doi.org/10.1109/ACCESS.2025.3587245
297. Missing Data Handling: A Comprehensive Review, Taxonomy, and Comparative Evaluation I. Chourib https://doi.org/10.4236/jcc.2025.136006
298. Non-parameterized ship maneuvering model of Deep Neural Networks based on real voyage data-driven Z. Wang et al. https://doi.org/10.1016/j.oceaneng.2023.115162
299. Predictive Wireless Channel Modeling of MmWave Bands Using Machine Learning A. Aldosary et al. https://doi.org/10.3390/electronics10243114
300. A new approach for porosity and permeability prediction from well logs using artificial neural network and curve fitting techniques: A case study of Niger Delta, Nigeria J. Urang et al. https://doi.org/10.1016/j.jappgeo.2020.104207
301. Determination of robust weights hidden layers on backpropagation algorithm to analyze coefficient drag high-speed train S. Adityo et al. https://doi.org/10.1088/1742-6596/1511/1/012074
302. Regionalization of Rainfall Regimes Using Hybrid RF-Bs Couple with Multivariate Approaches M. Ahmad Basri et al. https://doi.org/10.3390/ijgi10100689
303. Diurnal time–activity budget and habitat use of Whooping Cranes ( Grus americana ) in the reintroduced Louisiana nonmigratory population P. Vasseur et al. https://doi.org/10.1676/22-00039
304. Reconstruction of specific mass balance for glaciers in Western Himalaya using seasonal sensitivity characteristic(s) V. Gaddam et al. https://doi.org/10.1007/s12040-017-0839-6
305. Standard relationship between plasticity index and linear shrinkage: revisited F. Thaimo et al. https://doi.org/10.1680/jgeen.21.00085
306. Spatial Multi-Criteria Decision-Making Approach in Evaluating Walkability Indices: A Case Study of New York City S. Jokar et al. https://doi.org/10.66224/jgit.13.3.19
307. A hybrid retrieval framework for vegetation biophysical and biochemical traits using PRISMA-like data S. Hasti & M. Maralan https://doi.org/10.1080/01431161.2026.2720315
308. IRI Prediction using Machine Learning Models A. Sharma & P. Aggarwal https://doi.org/10.37394/232018.2023.11.10
309. Predictive Modeling for the Growth of Salmonella spp. in Liquid Egg White and Application of Scenario-Based Risk Estimation M. Kang et al. https://doi.org/10.3390/microorganisms9030486
310. Power Forecasting for Photovoltaic Microgrid Based on MultiScale CNN-LSTM Network Models H. Xue et al. https://doi.org/10.3390/en17163877
311. SIMRET: A Similarity-Guided Retinex Approach for Low-Light Enhancement A. Öztürk & F. Katırcıoğlu https://doi.org/10.3390/app16073517
312. Adapting the sampling design of research surveys to improve the biomass estimation of secondary species—the case study of Raja clavata D. Silva et al. https://doi.org/10.1093/icesjms/fsad089
313. Layout Optimization of FBG Sensor for Aluminum Alloy Beam Based on MOLA Multiobjective Optimization Algorithm J. Zhao et al. https://doi.org/10.1109/JSEN.2023.3276318
314. Predictive modeling and scenario-based risk estimation of Escherichia coli growth in meatball products: A comparison of aerobic and vacuum packaging conditions J. Park et al. https://doi.org/10.1016/j.lwt.2024.117271
315. A new intelligent model selection approach C. Bal & C. Aladag https://doi.org/10.1007/s00500-025-10910-7
316. A Novel Outlier-Robust Accuracy Measure for Machine Learning Regression Using a Non-Convex Distance Metric A. Hassanat et al. https://doi.org/10.3390/math12223623
317. Predicting terahertz properties in PCF-based Kagome lattice structure using deep learning M. Najm et al. https://doi.org/10.1016/j.ijleo.2026.172842
318. SSGRU: A novel hybrid stacked GRU-based traffic volume prediction approach in a road network P. Sun et al. https://doi.org/10.1016/j.comcom.2020.06.028
319. Intent-driven cloud resource design framework to meet cloud performance requirements and its application to a cloud-sensor system C. Wu et al. https://doi.org/10.1186/s13677-021-00242-w
320. Three-way formal concept clustering technique for matrix completion in recommender system C. G. & L. G.G. https://doi.org/10.1108/IJPCC-07-2019-0055
321. A novel metaheuristic optimization and soft computing techniques for improved hydrological drought forecasting O. Katipoğlu et al. https://doi.org/10.1016/j.pce.2024.103646
322. Density Estimation in Heritage Timber Elements Using Resistograph Drilling Resistance Y. Cabrera Martín et al. https://doi.org/10.3390/architecture6040180
323. Risk preferences over health: Empirical estimates and implications for medical decision-making K. Mulligan et al. https://doi.org/10.1016/j.jhealeco.2024.102857
324. A finite‐state machine‐based control design for thermal and state‐of‐charge balancing of lithium iron phosphate battery using flyback converters A. Zabetian‐Hosseini et al. https://doi.org/10.1002/bte2.20230055
325. Comparison of unstructured kinetic bacterial growth models. M. Muloiwa et al. https://doi.org/10.1016/j.sajce.2020.07.006
326. QSTR Analysis of Acute Rat Oral Toxicity of Amide Pesticides P. Banjare et al. https://doi.org/10.4018/IJQSPR.2020040103
327. Spatio-temporal analysis of extreme air pollution and risk assessment K. Rautela & M. Goyal https://doi.org/10.1016/j.jenvman.2024.123807
328. Evaluation of the CMIP5 GCM rainfall simulation over the Shire River Basin in Malawi P. Zuzani et al. https://doi.org/10.1007/s00704-022-04186-2
329. Predicting irregularities in arrival times for transit buses with recurrent neural networks using GPS coordinates and weather data O. Alam et al. https://doi.org/10.1007/s12652-020-02507-9
330. Prediction of enteric methane production, yield, and intensity in dairy cattle using an intercontinental database M. Niu et al. https://doi.org/10.1111/gcb.14094
331. Joint roughness profiling using photogrammetry I. Saricam & H. Ozturk https://doi.org/10.1007/s12518-022-00454-y
332. Nonlinear growth and body nutrient deposition models in Japanese quail (coturnix japonica) from 1-36 d D. Vieira et al. https://doi.org/10.1016/j.psj.2026.106555
333. Development of the MES criterion for brittle fracture prediction in V‐shaped notches under mixed mode I/II loading conditions S. Sajjadi et al. https://doi.org/10.1111/ffe.13464
334. Understanding of photosynthetically active radiation index under soil salinity variation using remote sensing practices in arid environments M. Elhag https://doi.org/10.5004/dwt.2018.21807
335. Compounding joint impact of rainfall, storm surge and river discharge on coastal flood risk: an approach based on 3D fully nested Archimedean copulas S. Latif & S. Simonovic https://doi.org/10.1007/s12665-022-10719-9
336. The effect of regular dental cast artifacts on the 3D superimposition of serial digital maxillary dental models E. Henninger et al. https://doi.org/10.1038/s41598-019-46887-1
337. TE-SDNet: Temporally Enhanced Sequential Dependency Network for photovoltaic power forecasting J. Zhang et al. https://doi.org/10.1016/j.aei.2026.105311
338. Hydroxylase Thermostability Prediction Based on Self-Trained Semisupervised Iteration and Bayesian Dynamic Tuning S. Liu et al. https://doi.org/10.1021/acs.jcim.6c00102
339. Avionics Graphics Hardware Performance Prediction with Machine Learning S. Girard et al. https://doi.org/10.1155/2019/9195845
340. Deep Neural Network with Attention and Station Embeddings for Robust Spatio-Temporal Multisensor Temperature Forecasting K. Abdalgader et al. https://doi.org/10.3390/agriengineering7120399
341. A Fuzzy Based Method For Diagnosis Of Acne Skin Disease Severity . Femi https://doi.org/10.26634/jpr.5.2.15537
342. Multi-label classification methods for green computing and application for mobile medical recommendations L. Guo et al. https://doi.org/10.1109/ACCESS.2016.2578638
343. Sar2color: Learning Imaging Characteristics of SAR Images for SAR-to-Optical Transformation Z. Guo et al. https://doi.org/10.3390/rs14153740
344. Predicting medication wastage using machine learning based on patient beliefs F. Aziz et al. https://doi.org/10.1177/20552076251355127
345. Assembly-oriented reliability analysis method for the top-connection structure of a nuclear fuel assembly Y. Liu et al. https://doi.org/10.1007/s41365-023-01247-7
346. Towards seasonal-based assessment of machine learning models in river dissolved oxygen simulations with different flow ranges N. Shiri et al. https://doi.org/10.1080/09715010.2025.2485301
347. Drought prediction: Insights from the fusion of LSTM and multi-source factors T. Wang et al. https://doi.org/10.1016/j.scitotenv.2023.166361
348. Paleoclimate data assimilation: Principles and prospects H. Zhang et al. https://doi.org/10.1007/s11430-024-1439-y
349. A multiscale modeling method for therapeutic antibodies in ion exchange chromatography D. Saleh et al. https://doi.org/10.1002/bit.28258
350. Artificial neural network-based flexible power point tracking for enhanced dynamic response of grid-connected photovoltaic systems N. Guerrero-Rodríguez et al. https://doi.org/10.1016/j.egyr.2025.10.018
351. Cascaded frameworks in underwater optical image restoration B. Li et al. https://doi.org/10.1016/j.inffus.2024.102809
352. Characterizations of air pollutants at roadside monitoring stations and traffic emission effects: A case study in Tianjin, China F. Zheng et al. https://doi.org/10.1016/j.jes.2024.09.018
353. Insights from utilizing data of different quality levels for simulating barley performance under Nordic conditions: The Agricultural Production Systems SIMulator model evaluation M. Appiah et al. https://doi.org/10.1093/insilicoplants/diae010
354. Uptake and fate of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in coastal marine biota determined using a stable isotopic tracer, 15N – [RDX] M. Ballentine et al. https://doi.org/10.1016/j.chemosphere.2016.03.038
355. FAL-YOLO: A Keypoint Detection Method for Harvest Crates in Farmland Environments Based on an Improved YOLOv8-Pose Algorithm J. Huang et al. https://doi.org/10.3390/agriculture16050570
356. A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine C. Liu et al. https://doi.org/10.1016/j.apenergy.2020.115383
357. Diagnosing long-term water quality degradation and pollution drivers through an explainable machine learning framework: A case study of the Bac hung Hai irrigation system (Vietnam) D. Kim & D. Nguyen https://doi.org/10.2166/wpt.2026.417
358. A fast reconstruction method of the dense point-cloud model for cultural heritage artifacts based on compressed sensing and sparse auto-encoder X. Chen et al. https://doi.org/10.1007/s11082-019-2038-y
359. Predicting the Residual Compressive Strength of Concrete Exposed to Elevated Temperatures Using Interpretable Machine Learning M. Noman et al. https://doi.org/10.1061/PPSCFX.SCENG-1536
360. Using improved gradient-boosted decision tree algorithm based on Kalman filter (GBDT-KF) in time series prediction L. Li et al. https://doi.org/10.1007/s11227-019-03130-y
361. ID-APM: Inverse Disparity-Guided Annealing Point Matching Approach for Robust ROI Localization in Blurred Thermal Images of Sika Deer C. Zhu et al. https://doi.org/10.3390/agriculture15192018
362. Development of the early warning model for oil produced water pollution and compliance with the guidelines using dimensional analysis L. Monatisa et al. https://doi.org/10.1016/j.jwpe.2023.103870
363. Comparison of forecasting performances: Does normalization and variance stabilization method beat GARCH(1,1)‐type models? Empirical evidence from the stock markets E. Gulay & H. Emec https://doi.org/10.1002/for.2478
364. Corrected multi-resolution ensemble model for wind power forecasting with real-time decomposition and Bivariate Kernel density estimation H. Liu & Z. Duan https://doi.org/10.1016/j.enconman.2019.112265
365. PV power forecast using a nonparametric PV model M. Almeida et al. https://doi.org/10.1016/j.solener.2015.03.006
366. Advances in Hybrid Evolutionary–Fuzzy Systems for Optimization and Intelligent Decision-Making Under Uncertainty: A Systematic Review H. Martínez Ángeles et al. https://doi.org/10.3390/math14122056
367. Combining CFD and ML to optimize biogas power plant agitation efficiency A. Heller et al. https://doi.org/10.1088/1361-6501/ae6718
368. Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour-Change Project R. West et al. https://doi.org/10.12688/wellcomeopenres.20000.2
369. High Performance Terahertz Circular Microstrip Antenna Optimized Using Machine Learning and Hybrid Photonic Band Gap Structures M. Reguig et al. https://doi.org/10.1007/s42979-026-05091-5
370. PM$$_{2.5}$$ forecasting based on transformer neural network and data embedding J. Limperis et al. https://doi.org/10.1007/s12145-023-01002-x
371. Assessing the accuracy of predictive models for numerical data: Not r nor r2, why not? Then what? J. Li & Q. Zhang https://doi.org/10.1371/journal.pone.0183250
372. A stacked machine learning model for the vertical total electron content forecasting E. Asamoah et al. https://doi.org/10.1016/j.asr.2024.04.055
373. Comparative Analysis of Electrode Configurations for Estimating Respiratory Effort From Diaphragmatic Electromyography G. Grońska et al. https://doi.org/10.1109/OJIM.2026.3709410
374. Forecasting coking coal prices by means of ARIMA models and neural networks, considering the transgenic time series theory M. Matyjaszek et al. https://doi.org/10.1016/j.resourpol.2019.02.017
375. Sequential Gaussian simulation predicts soil liquefaction potential Y. Zhang et al. https://doi.org/10.1080/1064119X.2024.2341997
376. Trend analysis of simulated streamflows via NARX-RNN and under CMIP6 climate scenarios in the Amazon River basin A. de Cássia Lobato Soares et al. https://doi.org/10.1007/s00521-026-12146-4
377. A new method for cross-calibration between LIBS systems based on a domain adaptive fully connected network X. Wang et al. https://doi.org/10.1039/D3JA00359K
378. Climatic conditions at provenance origin influence growth stability to changes in climate in two major tree species A. Di Fabio et al. https://doi.org/10.3389/ffgc.2024.1422165
379. SSA-LSTM-Multi-Head Attention Modelling Approach for Prediction of Coal Dust Maximum Explosion Pressure Based on the Synergistic Effect of Particle Size and Concentration Y. Liu et al. https://doi.org/10.32604/cmes.2025.064179
380. Adjusted CBA-Wheat model for predicting aboveground biomass in winter wheat from hyperspectral data J. Chen et al. https://doi.org/10.1016/j.fcr.2025.110060
381. Explainable machine learning reveals nonlinear human-environment relationships in mid-holocene settlement patterns across China F. Gao et al. https://doi.org/10.1016/j.palaeo.2026.113850
382. Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model M. Hou et al. https://doi.org/10.3390/en11123415
383. An Approach for 3D Modeling of the Regular Relief Surface Topography Formed by a Ball Burnishing Process Using 2D Images and Measured Profilograms S. Slavov et al. https://doi.org/10.3390/s23135801
384. Predicting Team Well-Being through Face Video Analysis with AI M. Müller et al. https://doi.org/10.3390/app14031284
385. Towards Virtual 3D Asset Price Prediction Based on Machine Learning J. Korbel et al. https://doi.org/10.3390/jtaer17030048
386. Predicting groundwater quality for irrigation suitability on agricultural practices using machine learning, fuzzy logic and GIS techniques M. Rhishi Hari Raj et al. https://doi.org/10.1016/j.pce.2025.104106
387. Predictability of Biodiesel Fuel Properties from the Fatty Acid Composition of the Feedstock Oils S. Kumar et al. https://doi.org/10.1007/s13369-021-05564-0
388. Predicting fuel properties of biomass using thermogravimetry and multivariate data analysis A. Strandberg et al. https://doi.org/10.1016/j.fuproc.2016.10.021
389. Performance of tree-based ensemble techniques in predicting groundwater quality for irrigation purposes A. Ouali et al. https://doi.org/10.1007/s12665-025-12469-w
390. Is it possible to improve the quality of predictions from an “intelligent” use of multiple QSAR/QSPR/QSTR models? K. Roy et al. https://doi.org/10.1002/cem.2992
391. Numerical Geometric Evaluation of an L-Shaped Oscillating Water Column Wave Energy Converter Under the Realistic Sea State Found in Rio Grande-RS M. Paiva et al. https://doi.org/10.3390/pr13123942
392. Conceptual cost estimation of highway bid unit prices using ordinary kriging B. Awuku et al. https://doi.org/10.1080/15623599.2022.2156844
393. Modelling Ionospheric Phenomena and Assessing the Performance of IRIPlas2017 during Different Phases of Solar Cycle 24 Y. Kayode et al. https://doi.org/10.3103/S0884591325020035
394. Optimized segmented regression models for the transition period of intervention effects X. Zhang et al. https://doi.org/10.1186/s41256-023-00312-3
395. Enhancing wide-band trajectory tracking and finite-time control of Dielectric Elastomer Actuators using Nonsingular terminal sliding mode control scheme S. Kassim et al. https://doi.org/10.1016/j.mechatronics.2025.103336
396. Assessment of Direct Normal Irradiance Forecasts Based on IFS/ECMWF Data and Observations in the South of Portugal J. Perdigão et al. https://doi.org/10.3390/forecast2020007
397. Queue Length Estimation at Motorcycle-dominated Signalised Intersection by Using Computer Vision and K-Means Clustering T. Vu et al. https://doi.org/10.1007/s13177-026-00634-9
398. Comprehensive Model for Real Battery Simulation Responsive to Variable Load G. Fenner et al. https://doi.org/10.3390/en14113209
399. Forecasting Indonesian food price inflation with multivariate time series and machine learning approaches A. Alfarrel Ghazali et al. https://doi.org/10.62189/ci.1695546
400. Optimizing mix design of concrete with manufactured sand for low embodied carbon and desired strength using machine learning Q. Ren et al. https://doi.org/10.1016/j.conbuildmat.2024.139407
401. Application of Support Vector Regression in Krylov Solvers R. Thalib et al. https://doi.org/10.33166/AETiC.2021.05.022
402. A Comprehensive Benchmarking of Classical and Deep Learning Models for Global Earthquake Magnitude Prediction H. Tanyıldız et al. https://doi.org/10.29132/ijpas.1838407
403. Comprehensive Assessment of Indoor Thermal in Vernacular Building Using Machine Learning Model with GAN-Based Data Imputation: A Case of Aceh Region, Indonesia M. Muslimsyah et al. https://doi.org/10.3390/buildings15142448
404. Prediction of f-CaO content in cement clinker: A novel prediction method based on LightGBM and Bayesian optimization X. Hao et al. https://doi.org/10.1016/j.chemolab.2021.104461
405. Complex terrains and wind power: enhancing forecasting accuracy through CNNs and DeepSHAP analysis T. Konstantinou & N. Hatziargyriou https://doi.org/10.3389/fenrg.2023.1328899
406. Estimation of Soil Cohesion Using Machine Learning Method: A Random Forest Approach H. Ly et al. https://doi.org/10.1155/2021/8873993
407. Maximum power tracking of variable‐speed wind energy conversion systems based on a near‐optimal servomechanism control system B. Sarsembayev et al. https://doi.org/10.1002/oca.2863
408. Evaluation of reference evapotranspiration methods for the northeastern region of India P. Pandey et al. https://doi.org/10.1016/j.iswcr.2016.02.003
409. Performance of non-laboratory Framingham risk scores using self-reported data for remote cardiovascular risk assessment L. de Menezes-Júnior https://doi.org/10.1038/s41598-025-27008-7
410. Assessment of different techniques for 3D superimposition of serial digital maxillary dental casts on palatal structures G. Vasilakos et al. https://doi.org/10.1038/s41598-017-06013-5
411. The Pearson Type IV distribution function employed to describe the parametric flow hydrograph B. Baziak & W. Gądek https://doi.org/10.1007/s11600-019-00327-w
412. Machine Learning-Based Comparative Analysis on Direct and Indirect Mapping of Soil Texture Types Through Soil Particle Size Fractions Using Multi-Source Remote Sensing J. Liu et al. https://doi.org/10.3390/agriculture15131395
413. BERT-AmPEP60: A BERT-Based Transfer Learning Approach to Predict the Minimum Inhibitory Concentrations of Antimicrobial Peptides for Escherichia coli and Staphylococcus aureus J. Cai et al. https://doi.org/10.1021/acs.jcim.4c01749
414. Utilizing Ensemble Learning and Dimension Reduction in Predicting Stock Prices: A Transparent Methodology with Insights from Explainable AI N. Das et al. https://doi.org/10.1007/s42979-024-03617-3
415. A GA-stacking ensemble approach for forecasting energy consumption in a smart household: A comparative study of ensemble methods M. Dostmohammadi et al. https://doi.org/10.1016/j.jenvman.2024.121264
416. A coupled model to improve river water quality prediction towards addressing non-stationarity and data limitation S. Chen et al. https://doi.org/10.1016/j.watres.2023.120895
417. In silico prediction of the developmental toxicity of diverse organic chemicals in rodents for regulatory purposes N. Basant et al. https://doi.org/10.1039/C5TX00493D
418. Estimation of a physical activity energy expenditure with a patch‐type sensor module using artificial neural network K. Kang et al. https://doi.org/10.1002/cpe.5455
419. Predicting river bathymetry in data sparse regions using a generative deep learning model C. Liang & V. Merwade https://doi.org/10.1016/j.jhydrol.2025.134450
420. Multispectral Pansharpening Based on Multisequence Convolutional Recurrent Neural Network P. Wang et al. https://doi.org/10.1109/JSTARS.2022.3218367
421. A comparative analysis of machine learning models for predicting groundwater and surface water in a stressed semi-arid watershed: The Khanmirza case study Z. Ebrahimzadeh et al. https://doi.org/10.1007/s12665-025-12801-4
422. Validation of standard ocean-color chlorophyll-a products in turbid coastal waters: A case study on statistical evaluation and quality control tests in the Persian Gulf M. Moradi & M. Zoljoodi https://doi.org/10.1016/j.jmarsys.2023.103875
423. Spatiotemporal distributions of pan evaporation and the influencing factors in China from 1961 to 2017 Z. Niu et al. https://doi.org/10.1007/s11356-021-15386-0
424. Synergistic Climate and Water-Quality Benefits from Wetland Restoration: A Long-Term Assessment Using Integrated Remote Sensing and Machine Learning S. Sajida et al. https://doi.org/10.1007/s13157-026-02111-1
425. Using temperature to predict the end of flowering in the common grape (Vitis vinifera) in the Macerata wine region, Italy M. Gentilucci & P. Burt https://doi.org/10.1007/s41207-018-0079-4
426. Benchmarking Machine Learning and Deep Learning Models for Groundwater Level Prediction in Karst Aquifers: The Dominant Role of Hydrogeological Complexity Q. Zhu et al. https://doi.org/10.3390/w18080939
427. SubvectorS_Geo: A Neural-Network-Based IPv6 Geolocation Algorithm Z. Ma et al. https://doi.org/10.3390/app13020754
428. Data-Driven Yield Improvement in Upstream Bioprocessing of Monoclonal Antibodies: A Machine Learning Case Study B. Strüssmann et al. https://doi.org/10.3390/pr13113394
429. Machine learning-driven optimization of photonic crystal structures for superior optical NOR gate performance F. Parandin et al. https://doi.org/10.1364/AO.529142
430. High-Pressure Fluid-Phase Equilibria and Henry’s Constants of Supercritical Gases in Ammonia E. Mace & J. Vrabec https://doi.org/10.1021/acs.jced.3c00327
431. Kinetic and Thermodynamic Study of Vacuum Residue Cracking over Cerium-Modified Metakaolinite Catalyst O. Al-Ameri et al. https://doi.org/10.3390/pr13103126
432. Improving the predictive accuracy of machine learning models for ceramic glaze gloss via feature engineering J. Choi et al. https://doi.org/10.1007/s41779-025-01318-5
433. Land cover classification using contextual texture information in sentinel-2 images of southern Mexico B. Flores-Rojas et al. https://doi.org/10.1007/s00521-025-11766-6
434. SpectraSensML Software: Mastering Complete Spectral Information for Luminescence Thermometry 2.0 A. Ćirić et al. https://doi.org/10.3390/make8080238
435. Clustering method and sine cosine algorithm for image segmentation L. Khrissi et al. https://doi.org/10.1007/s12065-020-00544-z
436. Quantitative analysis of breast cancer diagnosis using a probabilistic modelling approach S. Liu et al. https://doi.org/10.1016/j.compbiomed.2017.11.014
437. Inverse Matrix Problem in Regression for High‐Dimensional Data Sets N. Shakeel et al. https://doi.org/10.1155/2023/2308541
438. Thermodynamics and kinetics of water vapor adsorption in isolated kerogen: Evidence from experiments and molecular dynamics simulations Z. Liang et al. https://doi.org/10.1016/j.jgsce.2025.205703
439. Forecasting of abnormalities in optical glass lens centering using acoustic emissions S. Shiu et al. https://doi.org/10.1007/s40430-025-05729-0
440. A monthly-adaptive sky temperature model for the Mediterranean area based on symbolic regression: development, validation and impact on building energy simulations L. Evangelisti et al. https://doi.org/10.1016/j.enbuild.2025.116910
441. Otomatik Düşüncelere Makine Öğrenme Yöntemlerinin Uygulanması ile Aleksitimi Düzeyinin Tahmini M. YÖNTEM & K. ADEM https://doi.org/10.18863/pgy.554788
442. An effective parameter estimation on thermoelectric devices for power generation based on multiverse optimization algorithm L. Grisales-Noreña et al. https://doi.org/10.1016/j.rineng.2025.104408
443. Analyzing the Factors Affecting the Price of Broiler Chicken in Turkey Using the Boosting Regression Method M. Arikan et al. https://doi.org/10.1590/1806-9061-2021-1618
444. Monitoring Soil Salinity in the Harran Plain: A Comparative Analysis of Machine Learning Algorithms Using Two Different Scenarios with Sentinel-2 Data F. Kaplan et al. https://doi.org/10.1134/S1064229325604706
445. Rainfall Frequency Analysis Using Assessed and Corrected Satellite Precipitation Products in Moroccan Arid Areas. The Case of Tensift Watershed A. El Alaoui El Fels et al. https://doi.org/10.1007/s41748-021-00290-x
446. Regional significant wave height forecast in the East China Sea based on the Self-Attention ConvLSTM with SWAN model G. Li et al. https://doi.org/10.1016/j.oceaneng.2024.119064
447. Temporal evolution of morphological and luminescent properties in e-beam deposited strontium aluminate thin films doped with europium and dysprosium D. Kshatri et al. https://doi.org/10.1007/s11696-026-04946-8
448. Advancing hybrid modeling of Saccharomyces cerevisiae fermentation with mixed carbon sources and urea in a mini-stirred tank reactor J. Valencia-Velásquez et al. https://doi.org/10.1007/s00449-025-03222-5
449. Electricity demand forecasting for Tetouan, Morocco using Darts in machine-learning: A comparative study of forecasting models N. Biswas et al. https://doi.org/10.1016/j.rineng.2026.110289
450. Objective scoring of psoriasis area and severity index in 2D RGB images using deep learning R. Raj et al. https://doi.org/10.1007/s11042-024-18138-7
451. การประยุกต์ใช้โครงข่ายประสาทเทียมที่รับรู้ฟิสิกส์ (PINNs) เพื่อการจำลองการเคลื่อนที่ของน้ำในดินไม่อิ่มตัวตามสมการริชาร์ด อ. โคแหละ & เ. โฆสิตสกุลชัย https://doi.org/10.56825/jstku.2026.1524804
452. Metaheuristic-based prediction of flexural strength and dual-objective optimization for circular concrete-filled steel tubes S. Zhang et al. https://doi.org/10.1016/j.compstruct.2025.119464
453. Explainable AI in drought forecasting A. Dikshit & B. Pradhan https://doi.org/10.1016/j.mlwa.2021.100192
454. Seçili Temel Tarım Ürünleri Fiyatlarının Belirleyicileri: Türkiye Üzerine Bir Uygulama Y. Çolak & A. Sandalcılar https://doi.org/10.29216/ueip.1686663
455. Assessing the radiometric consistency of Gaofen-6 WFV and Sentinel-2 MSI multispectral reflectance for harmonization J. Tian et al. https://doi.org/10.1080/10095020.2025.2567560
456. A new model of air quality prediction using lightweight machine learning N. Van et al. https://doi.org/10.1007/s13762-022-04185-w
457. Efficacy of Tree-Based Models for Pipe Failure Prediction and Condition Assessment: A Comprehensive Review M. Latifi et al. https://doi.org/10.1061/JWRMD5.WRENG-6334
458. Operational river stage forecasting in a data-scarce delta: prophet model performance across multiple lead times and hydrometeorological input scenarios M. Islam et al. https://doi.org/10.2166/wpt.2026.365
459. Risk score prediction model based on single nucleotide polymorphism for predicting malaria: a machine learning approach K. Tai et al. https://doi.org/10.1186/s12859-022-04870-0
460. Evaluation and Development of a Predictive Model for Geophysical Well Log Data Analysis and Reservoir Characterization: Machine Learning Applications to Lithology Prediction A. Mishra et al. https://doi.org/10.1007/s11053-022-10121-z
461. Daily river flow forecasting using ensemble empirical mode decomposition based heuristic regression models: Application on the perennial rivers in Iran and South Korea M. Rezaie-Balf et al. https://doi.org/10.1016/j.jhydrol.2019.03.046
462. Cold Sprayed Metallic Coatings on Fibre-Reinforced Composites: A Machine Learning Approach for the Optimization of the Process A. Perna et al. https://doi.org/10.4028/p-7019v8
463. Evaluation of Turkey’s Road-Based Greenhouse Gas Inventory and Future Projections Ş. Çetin Doğruparmak et al. https://doi.org/10.3390/app15137007
464. The statistical neural network-based regression approach for prediction of optical band gap of CuO S. Ruzgar & E. Acar https://doi.org/10.1007/s12648-022-02283-6
465. Communication-efficient distributed quantile regression neural networks via convolution smoothing and poisson sampling C. Hao et al. https://doi.org/10.1016/j.eswa.2026.134604
466. Comparing and transforming PROMIS utility values to the EQ-5D J. Hartman & B. Craig https://doi.org/10.1007/s11136-017-1769-0
467. Quantifying suitable dynamic water levels in marsh wetlands based on hydrodynamic modelling P. Hu et al. https://doi.org/10.1002/hyp.14054
468. Progress and challenges in high-vanadium high-speed steel for shield machine cutter tools D. Wang et al. https://doi.org/10.1007/s10853-025-11999-9
469. Improving Air Pollution Modelling in Complex Terrain with a Coupled WRF–LOTOS–EUROS Approach: A Case Study in Aburrá Valley, Colombia J. Hinestroza-Ramirez et al. https://doi.org/10.3390/atmos14040738
470. IoT-based intelligent waste management system M. Ahmed et al. https://doi.org/10.1007/s00521-023-08970-7
471. Prediction of the temperature profiles using the generative model and the stacking ensemble method in a marginal sea K. Jung et al. https://doi.org/10.1016/j.acags.2026.100341
472. The Grade of Breathiness Index (GBI): A Fuzzy Logic Model for Vocal Assessment G. de Queiroz et al. https://doi.org/10.1016/j.jvoice.2026.03.001
473. Forecasting the Spread and Mortality Trends of COVID-19 in Afghanistan and Iran Using Long Short-Term Memory Neural Networks M. Jafari https://doi.org/10.61438/sarj.v1i2.145
474. Rapid identification of reactivity for the efficient recycling of coal fly ash: Hybrid machine learning modeling and interpretation C. Qi et al. https://doi.org/10.1016/j.jclepro.2022.130958
475. Spatiotemporal estimation of TROPOMI NO2 column with depthwise partial convolutional neural network Y. Lops et al. https://doi.org/10.1007/s00521-023-08558-1
476. An improved maize normalized root length density model based on water consumption and nitrogen application Y. Li et al. https://doi.org/10.1016/j.agwat.2025.110004
477. Evaluating deep learning time series models for PM2.5 forecasting across diverse horizons L. Zeng et al. https://doi.org/10.1016/j.isci.2026.114770
478. In silico studies on potential TNKS inhibitors: a combination of pharmacophore and 3D-QSAR modelling, virtual screening, molecular docking and molecular dynamics J. Liu et al. https://doi.org/10.1080/07391102.2018.1528887
479. Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement M. Hannan et al. https://doi.org/10.1038/s41467-020-17623-5
480. Process-aware SSA-Conv-PatchTST for robust multi-horizon aeration-demand forecasting in full-scale wastewater treatment plants R. Song et al. https://doi.org/10.1016/j.jwpe.2026.110584
481. Building performance evaluation through a novel feature selection algorithm for automated arx model identification procedures D. Antonucci et al. https://doi.org/10.1016/j.enbuild.2017.06.009
482. Sentiment analysis based distributed recommendation system T. Singh et al. https://doi.org/10.1007/s11042-023-18081-z
483. Stable but stressed: Investigating vegetation dynamics in the Sinharaja Rainforest using satellite NDVI and climate-driven machine learning models M. Nuskiya et al. https://doi.org/10.30493/DAS.2026.012706
484. Rapid loss of maternal immunity and increase in environmentally mediated antibody generation in urban gulls J. Lamb et al. https://doi.org/10.1038/s41598-024-54796-1
485. Performance study of a dual-function roof solar collector for Chinese traditional buildings application Z. Hu et al. https://doi.org/10.1016/j.applthermaleng.2017.09.019
486. Uso de las TIC y relación con los Objetivos de Desarrollo Sostenible en Ecuador J. Ibujés Villacís & A. Franco Crespo https://doi.org/10.17163/ret.n17.2019.03
487. Ornstein-Uhlenbeck process and GARCH model for temperature forecasting in weather derivatives valuation B. Žmuk & M. Kovač https://doi.org/10.2478/crebss-2020-0003
488. Salp Swarm Optimization Algorithm for Estimating the Parameters of Photovoltaic Panels Based on the Three-Diode Model J. Montano et al. https://doi.org/10.3390/electronics10243123
489. Decoding the dynamics of daily total global solar radiation: Computational learning strategies powered by explainable AI M. Akiner et al. https://doi.org/10.1016/j.jer.2025.10.008
490. Automated Assessment of Movement Impairment in Huntington’s Disease M. Bennasar et al. https://doi.org/10.1109/TNSRE.2018.2868170
491. Density estimation method of mature wheat based on point cloud segmentation and clustering R. Zou et al. https://doi.org/10.1016/j.compag.2023.107626
492. Deformation Energy Estimation of Cherry Tomato Based on Some Engineering Parameters Using Machine-Learning Algorithms O. Kabas et al. https://doi.org/10.3390/app13158906
493. A comparison of forecasting models for the resource usage of MapReduce applications Y. Li et al. https://doi.org/10.1016/j.neucom.2020.07.059
494. Determination of the natural potential groundwater recharge in the Valle Alto basin, Bolivia, through a soil water balance C. Apaza-Coria et al. https://doi.org/10.1007/s10040-022-02553-x
495. Experience-Based Swedish TTO and VAS Value Sets for EQ-5D-5L Health States K. Burström et al. https://doi.org/10.1007/s40273-020-00905-7
496. Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin, Mexico J. Ávila‐Carrasco et al. https://doi.org/10.1111/1752-1688.12672
497. Characterization of moderate or intense low-oxygen dilution (MILD) combustion regimes and NOX emissions in ammonia and hydrogen-enriched ammonia mixtures Z. Shah et al. https://doi.org/10.1016/j.ijhydene.2026.156325
498. Predictive model for growth of Bacillus cereus during cooling of cooked rice V. Juneja et al. https://doi.org/10.1016/j.ijfoodmicro.2018.09.023
499. ANFIS Parallelization Control on Triple-Axis Sun Tracker to Minimize Solar Rays Incidence Angle on Photovoltaic H. Lastya et al. https://doi.org/10.1109/ACCESS.2025.3542337
500. A novel prediction approach of three-dimensional thermal fatigue cracks in thermal compression bonding electrodes based on digital twin Q. Ren et al. https://doi.org/10.1371/journal.pone.0339003
501. Spatio-Temporal Feature Pyramid Interactive Attention Network for Egocentric Gaze Prediction M. Yuan & D. Xu https://doi.org/10.1109/TCSVT.2023.3258962
502. A review of object detection based on deep learning Y. Xiao et al. https://doi.org/10.1007/s11042-020-08976-6
503. Evaluating the suitability of the GlobalBuildingAtlas for digital urban infrastructure analysis in India G. Dandabathula et al. https://doi.org/10.1088/2634-4505/ae7f49
504. Closed-Form Equations for the Reorder Point and Order-Up-To Level in a Lost-Sales Periodic-Review (R, s, S) Inventory Policy S. Žic & J. Žic https://doi.org/10.3390/math14132424
505. Comparing Energy-Based Criterion with Strain-Based Criterion for Predicting Brittle Fracture in V-Shaped Notches under Mixed-Mode I/II Loading Conditions S. Sajjadi et al. https://doi.org/10.1134/S1029959921030073
506. A comprehensive evaluation of photovoltaic simulation software: A decision-making approach using Analytic Hierarchy Process and performance analysis M. Islam et al. https://doi.org/10.1016/j.esr.2025.101663
507. Aggregation of cognitive networks in high-uncertainty modeling scenarios M. Quesada et al. https://doi.org/10.1016/j.neucom.2026.135249
508. An Empirical, Functional approach to Depth Damages W. Lehman et al. https://doi.org/10.1051/e3sconf/20160705002
509. Advanced spatio temporal modeling with geographically and temporally weighted spline regression (GTWSR) for strategic food price forecasting in Indonesia . Sifriyani et al. https://doi.org/10.1016/j.mex.2025.103727
510. Comparative analysis of optimized LSTM architectures for long-term solar power forecasting M. Türker et al. https://doi.org/10.35860/iarej.1794285
511. Estimation of permeability of soil using easy measured soil parameters: assessing the artificial intelligence-based models B. Singh et al. https://doi.org/10.1080/09715010.2019.1574615
512. Application of multispectral imaging combined with machine learning methods for rapid and non-destructive detection of zearalenone (ZEN) in maize W. Liu et al. https://doi.org/10.1016/j.measurement.2022.111944
513. Proof of Concept: Calibration of an Overhead Line Conductors’ Movements Simulation Model Using Ensemble-Based Machine Learning Model H. Amroun et al. https://doi.org/10.1109/ACCESS.2021.3131391
514. Robust Spatio-temporal reconstruction of XCO₂ using OCO-2 and OCO-3 satellite observations and deep learning-based uncertainty quantification M. Awad & S. Homayouni https://doi.org/10.1016/j.nexres.2026.101707
515. Predicting construction cost index using fuzzy logic and machine learning in Jordan H. Al Kailani et al. https://doi.org/10.1108/CI-08-2023-0182
516. Geospatial approach to study the spatial distribution of major soil nutrients in the Northern region of Ghana M. Antwi et al. https://doi.org/10.1080/23312041.2016.1201906
517. Evaluation of methods for selecting climate models to simulate future hydrological change A. Ross & R. Najjar https://doi.org/10.1007/s10584-019-02512-8
518. A novel hybrid artificial intelligence approach for flood susceptibility assessment K. Chapi et al. https://doi.org/10.1016/j.envsoft.2017.06.012
519. Predictive modeling and probabilistic risk assessment of Clostridium perfringens in hamburgers and sandwiches Y. Choi et al. https://doi.org/10.1007/s10068-021-01000-z
520. Developing a Data Mining Based Model to Extract Predictor Factors in Energy Systems: Application of Global Natural Gas Demand R. Hafezi et al. https://doi.org/10.3390/en12214124
521. Prediction of soil organic matter content by combining data from Nix ProTM color sensor and portable X-ray fluorescence spectrometry in tropical soils A. Faria et al. https://doi.org/10.1016/j.geodrs.2021.e00461
522. Leveraging random forest techniques for enhanced microbiological analysis: a machine learning approach to investigating microbial communities and their interactions D. Chrobak et al. https://doi.org/10.51582/interconf.19-20.04.2023.040
523. Integrated sensing device for irrigation scheduling: field evaluation and crop water stress index estimation of wheat A. Kumari et al. https://doi.org/10.2166/wpt.2024.102
524. Exploring the spatial differentiation of urbanization on two sides of the Hu Huanyong Line -- based on nighttime light data and cellular automata D. Chen et al. https://doi.org/10.1016/j.apgeog.2019.102081
525. A potential bioelectrical impedance equation for estimating skeletal muscle area using computed tomography in colorectal cancer A. de Sousa Rebouças et al. https://doi.org/10.1038/s41598-025-17872-8
526. Climate and local environment co-mediate the taxonomic and functional diversity of bacteria and archaea in the Qinghai-Tibet Plateau rivers Y. Wu et al. https://doi.org/10.1016/j.scitotenv.2023.168968
527. Ensemble machine learning algorithms for efficient prediction of compressive strength of concrete containing tyre rubber and brick powder D. Sinkhonde et al. https://doi.org/10.1016/j.clwas.2025.100236
528. Predictive Modeling of Lignin Content for the Screening of Suitable Poplar Genotypes Based on Fourier Transform–Raman Spectrometry W. Gao et al. https://doi.org/10.1021/acsomega.1c00400
529. Molecular modeling studies of benzothiophene-containing derivatives as promising selective estrogen receptor downregulators: a combination of 3D-QSAR, molecular docking and molecular dynamics simulations C. Zhang et al. https://doi.org/10.1080/07391102.2020.1751717
530. An ensemble-based assessment of bias adjustment performance, changes in hydrometeorological predictors and compound extreme events in EAS-CORDEX P. Olschewski et al. https://doi.org/10.1016/j.wace.2022.100531
531. Data-driven parametric adaption in type-2 fuzzy logic for significant pattern discovery using massive heterogeneous data in cognitive IoT V. Jha & P. Tripathi https://doi.org/10.1007/s13748-025-00380-1
532. Long short-term memory prediction for COVID19 time series M. Milivojević & A. Gavrovska https://doi.org/10.5937/telfor2102081M
533. Detection and counting of root-knot nematodes using YOLO models with mosaic augmentation T. Pun et al. https://doi.org/10.1016/j.biosx.2023.100407
534. Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures R. Hasanzadeh Nafari et al. https://doi.org/10.5194/nhess-17-1047-2017
535. Rapid characterization of MSW and RDF feedstocks for waste-to-energy process using LIBS and ML techniques J. Liu et al. https://doi.org/10.1016/j.wasman.2025.115079
536. End-effector picking-pose estimation for tomato harvesting: a fusion approach combining instance segmentation and optimised point-cloud fitting Z. Cui et al. https://doi.org/10.1016/j.aiia.2026.09.011
537. Warfarin dosing algorithms: A systematic review I. Asiimwe et al. https://doi.org/10.1111/bcp.14608
538. Data Restoration by Linear Estimation of the Principal Components From Lossy Data Y. Lee & S. Choi https://doi.org/10.1109/ACCESS.2020.3024809
539. PM10 concentration forecast using modified depth-first search and supervised learning neural network C. Photphanloet & R. Lipikorn https://doi.org/10.1016/j.scitotenv.2020.138507
540. Electromagnetic signal denoising model based on stacked ET layers structure Y. Huang et al. https://doi.org/10.1016/j.measurement.2024.115796
541. Predictive polynomial modeling and validation of mass attenuation coefficients for SrO-doped bioglasses K. Abushahla & H. Arslan https://doi.org/10.1088/1402-4896/ae01ec
542. Blue Carbon Modeling of Mangrove Forests in Muara Gembong Using the InVEST Model A. Jaelani et al. https://doi.org/10.1088/1755-1315/1624/1/012003
543. Pilot study GLIM criteria for categorization of a malnutrition diagnosis of patients undergoing elective gastrointestinal operations: A pilot study of applicability and validation J. Henrique et al. https://doi.org/10.1016/j.nut.2020.110961
544. Enhancing ERA5 precipitation with improved predictor selection for regional climate change assessment M. Keskin et al. https://doi.org/10.1007/s11069-025-07664-8
545. GEVReg-MIDAS-SSVS for Mixed-Frequency Time Series Interval Forecasting F. Zayyan et al. https://doi.org/10.1109/ACCESS.2026.3712031
546. Variable withdrawal elevations as a management tool to counter the effects of climate warming in Germany’s largest drinking water reservoir C. Mi et al. https://doi.org/10.1186/s12302-019-0202-4
547. Integrating machine learning and spatial clustering for malaria case prediction in Brazil’s Legal Amazon K. Monteiro et al. https://doi.org/10.1186/s12879-025-11193-x
548. Online Fault Detection in ReRAM-Based Computing Systems for Inferencing M. Liu & K. Chakrabarty https://doi.org/10.1109/TVLSI.2021.3139530
549. Ecological Momentary Assessment: A Systematic Review of Validity Research L. Stinson et al. https://doi.org/10.1007/s40614-022-00339-w
550. PMT: New analytical framework for automated evaluation of geo-environmental modelling approaches O. Rahmati et al. https://doi.org/10.1016/j.scitotenv.2019.02.017
551. Predicting Path Loss of an Indoor Environment Using Artificial Intelligence in the 28-GHz Band S. Aldossari https://doi.org/10.3390/electronics12030497
552. Graph neural network architectures for predicting the electrophilicity index: insights from 2D and 3D molecular graph representations S. Kumar & A. Bande https://doi.org/10.1039/D6CP00677A
553. Assessment of property estimation methods for the thermodynamics of carbon dioxide-based products K. Pacheco et al. https://doi.org/10.1016/j.enconman.2020.112756
554. A niche‐based theory of island biogeography G. Beaugrand et al. https://doi.org/10.1002/ece3.11540
555. An Approach Based on Fog Computing for Providing Reliability in IoT Data Collection: A Case Study in a Colombian Coffee Smart Farm A. Montoya-Munoz & O. Rendon https://doi.org/10.3390/app10248904
556. Integrating numerical and textual data for accurate rice yield prediction: A novel ensemble learning framework for regional agriculture M. Jabed et al. https://doi.org/10.1016/j.atech.2026.102486
557. Maize tassel number and tasseling stage monitoring based on near-ground and UAV RGB images by improved YoloV8 X. Yu et al. https://doi.org/10.1007/s11119-024-10135-y
558. Synergistic Effects of Bagasse Ash and Rice Husk Ash on the Fresh and Mechanical Properties of Ternary Blended Concrete: An Optimization Approach Using Response Surface Methodology A. Gora et al. https://doi.org/10.3390/eng7070355
559. Optimized Intersection Signal Timing: An Intelligent Approach-Based Study for Sustainable Models H. An et al. https://doi.org/10.3390/su141811422
560. Probing the binding mechanism of substituted pyridine derivatives as effective and selective lysine-specific demethylase 1 inhibitors using 3D-QSAR, molecular docking and molecular dynamics simulations Z. Wang et al. https://doi.org/10.1080/07391102.2018.1518158
561. Predicting Temperatures Inside a Steel Slab Reheating Furnace Using Neural Networks R. de Souza Lima et al. https://doi.org/10.1109/TIA.2025.3535838
562. Towards a Reliable Design of Geopolymer Concrete for Green Landscapes: A Comparative Study of Tree-Based and Regression-Based Models R. Wang et al. https://doi.org/10.3390/buildings14030615
563. Predicting the Experimental Results of the Tensile Strength of Parts Produced with a 3-D Printer Using ABS Filament with Artificial Intelligence S. Bacak & M. Şahin https://doi.org/10.1520/JTE20240564
564. Predicting relative species composition within mixed conifer forest pixels using zero-inflated models and Landsat imagery S. Savage et al. https://doi.org/10.1016/j.rse.2015.10.013
565. ST-DTGCN: spatiotemporal forecasting with dynamic transformer and graph convolution networks M. Shi et al. https://doi.org/10.1038/s41598-026-49419-w
566. A Fault Diagnosis Algorithm for Wind Turbine Blades Based on BP Neural Network J. Bi et al. https://doi.org/10.1088/1757-899X/1043/2/022032
567. Evaluation of chemical kinetic models for NH3/H2 fuel mixtures through laminar flame speed analysis D. Vo et al. https://doi.org/10.1016/j.ijhydene.2025.150412
568. Reliability Analysis of Pile Foundation Using ELM and MARS M. Kumar & P. Samui https://doi.org/10.1007/s10706-018-00777-x
569. Evaluating the accuracy of two simple field methods for estimating grassland curing state in the Dry Chaco Region of Argentina R. Coria https://doi.org/10.1080/15324982.2025.2611270
570. Mapping Seagrass Percent Cover And Biomass In Nusa Lembongan, Bali, Indonesia D. Br Ginting et al. https://doi.org/10.24057/2071-9388-2023-2886
571. Comparative analysis of deadwood abundance and characteristics in protected versus managed forests in Northeastern Turkey S. Özdemir et al. https://doi.org/10.1007/s11676-026-02028-9
572. A predictive growth model for Clostridium botulinum during cooling of cooked uncured ground beef V. Juneja et al. https://doi.org/10.1016/j.fm.2020.103618
573. Fingerprinting sediment sources using fallout radionuclides demonstrates that subsoil provides the major source of sediment in sub-humid Ethiopia T. Abere et al. https://doi.org/10.1007/s11368-025-03964-5
574. Prediction of Egg Weight in Japanese Quails (Coturnix coturnix japonica) with Internal Quality Traits Using Machine Learning Algorithms M. Eroğlu & S. Aslan https://doi.org/10.18016/ksutarimdoga.vi.1695149
575. Numerical Study of the Impact of Transverse Ribs on the Energy Potential of Air-Based BIPV/T Envelope Systems B. Nghana et al. https://doi.org/10.3390/en16145266
576. Developing Lotka–Volterra Based Models to Describe Bdellovibrio Predation in a Batch and Chemostat Experimental System A. Ogundero et al. https://doi.org/10.1111/1758-2229.70141
577. Envisioning Romania’s Path to Sustainable Development: A Prognostic Approach A. Ciucu-Durnoi et al. https://doi.org/10.3390/su151712671
578. Travel Time Estimation for Vehicles Using Link-Level Data Through Tree-Based Models N. Srivastava et al. https://doi.org/10.1007/s13177-025-00580-y
579. Algorithms predict morbidity and mortality of Saguaro Cacti (Carnegiea gigantea) from sunlight exposures L. Evans https://doi.org/10.1016/j.flora.2021.151775
580. Architecture Optimization of a Non-Linear Autoregressive Neural Networks for Mackey-Glass Time Series Prediction Using Discrete Mycorrhiza Optimization Algorithm H. Carreon-Ortiz et al. https://doi.org/10.3390/mi14010149
581. SWSA transformer: A forecasting method of ultra-short-term wind speed from an offshore wind farm using global attention mechanism S. Lin et al. https://doi.org/10.1063/5.0153511
582. AuditML: An Efficient Publicly Auditable Privacy-Preserving Framework for Machine Learning Inference Q. Li et al. https://doi.org/10.1109/TIFS.2026.3729507
583. Investigation on the indoor environment during a whole cooking process under constant make-up air organization in a Chinese-style residential kitchen Y. Liu et al. https://doi.org/10.1177/1420326X231152554
584. Accuracy of Implant Level Intraoral Scanning and Photogrammetry Impression Techniques in a Complete Arch with Angled and Parallel Implants: An In Vitro Study H. Tohme et al. https://doi.org/10.3390/app11219859
585. Assessing Potential Climate Change Impacts and Adaptive Measures on Rice Yields: The Case of Zhejiang Province in China Y. Guo et al. https://doi.org/10.3390/su11082372
586. Area-based scenario development in land-use change modeling: A system dynamics-assisted approach for mixed agricultural-residential landscapes O. Ghadirian et al. https://doi.org/10.1016/j.ecoinf.2023.102129
587. Adaptation of the Most Probable Precipitation Method for the Temporal Variability of the Precipitation Series A. Bărbulescu https://doi.org/10.3390/app16041768
588. The probability of improved prediction as a new concept for model selection in the presence of outliers O. Thas & S. Jaspers https://doi.org/10.1080/00949655.2025.2558863
589. Modeling for Survival of Clostridium perfringens in Saeng-sik, a Powdered Ready-to-Eat Food with Low Water Activity J. Park et al. https://doi.org/10.4315/0362-028X.JFP-18-368
590. Artificial intelligence for biodiversity: Exploring the potential of recurrent neural networks in forecasting arthropod dynamics based on time series S. Lhoumeau et al. https://doi.org/10.1016/j.ecolind.2025.113119
591. Dengue Epidemics Prediction: A Survey of the State-of-the-Art Based on Data Science Processes P. Siriyasatien et al. https://doi.org/10.1109/ACCESS.2018.2871241
592. The influence of campus characteristics, temporal factors, and weather events on campuses-related daily bike-share trips B. Kutela & H. Teng https://doi.org/10.1016/j.jtrangeo.2019.06.002
593. PortWeather: A Lightweight Onboard Solution for Real-Time Weather Prediction P. Karvelis et al. https://doi.org/10.3390/s20113181
594. Modeling future climate change impacts on hydrology using CORDEX data and QSWAT model in Ethiopia’s Upper Tekeze Basin G. Haile et al. https://doi.org/10.1007/s43621-025-02369-1
595. Spatiotemporal evaluation of precipitation and streamflow trends in the Upper Awash River Basin using multisource data (1990–2023) N. Bihon et al. https://doi.org/10.2166/aqua.2025.047
596. A Multiscale Hierarchical Model for Sparse Hyperspectral Unmixing J. Zou & J. Lan https://doi.org/10.3390/rs11050500
597. GIST-PM-Asia v1: development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia S. Lee et al. https://doi.org/10.5194/gmd-9-17-2016
598. Evaluating the efficacy of hybrid deep learning models in assessing temporal night-time light trends for the cities of Cape Town, Durban and Johannesburg in South Africa Z. Mncube et al. https://doi.org/10.3389/frsen.2026.1723667
599. Shoreline change rate detection applying the DSAS technique on low and medium resolution data: Case study along Ash Shu’aybah-Al Mujayrimah coastal Area of the Eastern Red Sea, Saudi Arabia O. Alharbi et al. https://doi.org/10.1016/j.rsma.2023.103118
600. Trajectory Privacy-Protection Mechanism Based on Multidimensional Spatial–Temporal Prediction J. Xi et al. https://doi.org/10.3390/sym16091248
601. Investigation of Numerical Beach Position Effects on the Hydrodynamics of a Submerged Horizontal Plate Device Under Sea State Conditions G. Thum et al. https://doi.org/10.3390/pr14121934
602. Assessment of the Accuracy of Close Distance Photogrammetric JRC Data D. Kim et al. https://doi.org/10.1007/s00603-016-1042-9
603. Methods for Comparing Simulated and Observed Satellite Infrared Brightness Temperatures and What Do They Tell Us? S. Griffin et al. https://doi.org/10.1175/WAF-D-16-0098.1
604. The effects of March 20 2015 solar eclipse on the F2 layer in the mid-latitude V. Chukwuma & B. Adekoya https://doi.org/10.1016/j.asr.2016.06.038
605. Statistically Modeling the Fatigue Life of Copper and Aluminum Wires Using Archival Data D. Harlow https://doi.org/10.3390/met13081419
606. A Comprehensive Evaluation of Machine Learning Algorithms for Digital Soil Organic Carbon Mapping on a National Scale D. Radočaj et al. https://doi.org/10.3390/app14219990
607. CISSKA-LSB: color image steganography using stego key-directed adaptive LSB substitution method K. Muhammad et al. https://doi.org/10.1007/s11042-016-3383-5
608. Predicting COVID-19 Confirmed Case in Surabaya using Autoregressive Integrated Moving Average, Bivariate and Multivariate Transfer Function A. Saikhu et al. https://doi.org/10.1088/1757-899X/1077/1/012055
609. An improved DFVMD-LSTM hybrid time series model for predicting total solar irradiance H. Chen et al. https://doi.org/10.13168/AGG.2023.0013
610. Comparative analysis of bias correction techniques for future climate assessment using CMIP6 hydrological variables for the Indian subcontinent M. Shah et al. https://doi.org/10.1007/s11600-024-01378-4
611. Varying influences of the built environment on daily and hourly pedestrian crossing volumes at signalized intersections estimated from traffic signal controller event data P. Singleton et al. https://doi.org/10.1016/j.jtrangeo.2021.103067
612. Machine learning in the prediction of sugarcane production environments G. Almeida et al. https://doi.org/10.1016/j.compag.2021.106452
613. Assessment of NCEP-CFSR Precipitation Products in Meteorological Drought Monitoring for The Citarum Basin H. Ihsan et al. https://doi.org/10.1088/1755-1315/286/1/012019
614. Land subsidence prediction in coal mining using machine learning models and optimization techniques S. Jahanmiri & M. Noorian-Bidgoli https://doi.org/10.1007/s11356-024-33300-2
615. Deep neural network for oil spill detection using Sentinel-1 data: application to Egyptian coastal regions S. Ahmed et al. https://doi.org/10.1080/19475705.2022.2155998
616. AIDPCP: an adaptive intelligent data preprocessing and clustering pipeline for obesity prediction with explainable AI M. Shibly et al. https://doi.org/10.1016/j.meadig.2026.100049
617. CPR-SAT: A context-aware pictogram recommendation system – a speech assistive technology B. Evangeline et al. https://doi.org/10.1016/j.softx.2026.102635
618. A machine learning and geostatistical hybrid method to improve spatial prediction accuracy of soil potentially toxic elements A. Molla et al. https://doi.org/10.1007/s00477-022-02284-1
619. TAPAS: Transient Absorption Processing and Analysis Software P. Frech & M. Scheele https://doi.org/10.1002/cptc.202500236
620. Application of machine learning in the study of cobalt-based oxide catalysts for antibiotic degradation: An innovative reverse synthesis strategy S. Jiang et al. https://doi.org/10.1016/j.jhazmat.2024.134309
621. Augmenting Knowledge for Individual NVR Prediction in Different Spatial and Temporal Cross-Building Environments M. Kim & S. Lee https://doi.org/10.3390/electronics13152901
622. A Method to Improve the Accuracy of Simulation Models: A Case Study on Photovoltaic System Modelling A. Bupi et al. https://doi.org/10.3390/en14020372
623. Predictive Model of Listeria monocytogenes Growth in Queso Fresco M. Thomas et al. https://doi.org/10.4315/0362-028X.JFP-19-185
624. Fractal Dispersion Pollutant Transport Modeling with Spatially Varying Sorption and Degradation Effect S. Rajput & M. Singh https://doi.org/10.1061/(ASCE)EE.1943-7870.0002031
625. An integrated data-driven approach using dual polarized SAR data for spatiotemporal analysis of water surface changes S. Bagheri et al. https://doi.org/10.1016/j.asr.2025.09.018
626. Identification and characterization of estuarine submesoscale fronts based on multisource high-resolution remote sensing R. Xu et al. https://doi.org/10.1016/j.jag.2026.105165
627. Metaheuristic Optimization of Random Forest for Predicting Punch Shear Strength of FRP-Reinforced Concrete Beams P. Yang et al. https://doi.org/10.3390/ma16114034
628. M2ECG: Wearable Mechanocardiograms to Electrocardiogram Estimation Using Deep Learning M. Tapotee et al. https://doi.org/10.1109/ACCESS.2024.3353463
629. Digital twin-enabled process simulation and thermal-state prediction for continuous carbon fiber-reinforced nylon fused filament fabrication L. Kan et al. https://doi.org/10.1007/s00170-026-18887-9
630. Sound prediction based on footstep-induced vibrations in concrete building using a convolutional neural network H. Shin et al. https://doi.org/10.1016/j.apacoust.2022.108965
631. Application of a machine learning-based prediction model for the design of general lighting systems in offices M. Yaşa & Ş. Yağmur https://doi.org/10.1016/j.rineng.2025.108774
632. SCADA-based early detection of wind turbine yaw motor current failures using Gaussian process surrogate models and Fisher's combined probabilistic alarm thresholding R. Pandit et al. https://doi.org/10.1016/j.weer.2026.100031
633. Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction S. Ghimire et al. https://doi.org/10.1016/j.rser.2019.109247
634. Energy Efficiency of Older Houses: A Parametric Optimisation Study on Retrofitting a 1930s House in Adelaide, Australia E. Chen et al. https://doi.org/10.3390/buildings16010131
635. A point-surface fusion method for vegetation water content retrievalconsidering optimization of GNSS sites and modeling elements Y. Liang et al. https://doi.org/10.1088/1361-6501/ac9f13
636. Persuasion-based recommender system ensambling matrix factorisation and active learning models R. Sánchez-Corcuera et al. https://doi.org/10.1007/s00779-020-01382-7
637. Ensemble and Hybrid Models in Automated Essay Scoring: A Literature Review V. Ramnarain-Seetohul et al. https://doi.org/10.1007/s42979-025-04245-1
638. Unavailable Transit Feed Specification: Making It Available With Recurrent Neural Networks L. Iovino et al. https://doi.org/10.1109/TITS.2021.3053373
639. Prediction of probability of liquefaction using hybrid ANN with optimization techniques D. Kumar et al. https://doi.org/10.1007/s12517-022-10855-3
640. Quantitative determination of auxiliary information for mapping soil heavy metals and soil contamination risk assessment L. Zeng et al. https://doi.org/10.1016/j.apgeochem.2021.104964
641. Machine learning-guided discovery of thermodynamically stable single-atom catalysts on functionalized MXenes for enhanced oxygen reduction and evolution reactions H. Guo & S. Lee https://doi.org/10.1039/D5TA02929E
642. A New Hybrid Approach to Forecast Wind Power for Large Scale Wind Turbine Data Using Deep Learning with TensorFlow Framework and Principal Component Analysis M. Khan et al. https://doi.org/10.3390/en12122229
643. Comparative study of the pore volume percentages of the carbonate core plug samples using direct, 2D techniques and exploratory data analysis E. Pirot et al. https://doi.org/10.1016/j.flowmeasinst.2025.102813
644. Effects of Air Pollution on Rainfall Microphysics Over the Yangtze River Delta Q. Yang et al. https://doi.org/10.1029/2021JD035934
645. On the Effectiveness of Feedforward Neural Networks for Performance Prediction in Highly Configurable Systems: The Case of Linux Kernel Size J. Bessa et al. https://doi.org/10.5753/jserd.2026.6399
646. Influencing factors and prediction of CO2 wettability in coal seams for carbon geo-storage: leveraging data-driven machine learning approaches A. Fernandez-Moncada & M. Arif https://doi.org/10.1016/j.fuel.2025.138041
647. Enhancing the reliability and accuracy of machine learning models for predicting carbonation progress in fly ash‐concrete: A multifaceted approach I. Uwanuakwa & P. Akpınar https://doi.org/10.1002/suco.202300912
648. EvatCrop: a novel hybrid quasi-fuzzy artificial neural network (ANN) model for estimation of reference evapotranspiration G. Banerjee et al. https://doi.org/10.7717/peerj.17437
649. A novel hybrid artificial intelligent approach based on neural fuzzy inference model and particle swarm optimization for horizontal displacement modeling of hydropower dam K. Bui et al. https://doi.org/10.1007/s00521-016-2666-0
650. A novel approach for rainfall-runoff modelling using a biogeography-based optimization technique B. Roy et al. https://doi.org/10.1080/15715124.2019.1628035
651. Performance metrics for guidance active constraints in surgical robotics N. Enayati et al. https://doi.org/10.1002/rcs.1873
652. Towards Rational Design of Confined Catalysis in Carbon Nanotube by Machine Learning and Grand Canonical Monte Carlo Simulations C. Yang et al. https://doi.org/10.1002/ange.202421552
653. Wind Estimation Methods for Nearshore Wind Resource Assessment Using High-Resolution WRF and Coastal Onshore Measurements T. Maruo & T. Ohsawa https://doi.org/10.3390/wind5030017
654. A dynamic predictive model for the growth of Salmonella spp. and Staphylococcus aureus in fresh egg yolk and scenario-based risk estimation J. Park et al. https://doi.org/10.1016/j.foodcont.2020.107421
655. Accelerating the design and optimization of catalysts for the hydrogen evolution reaction in transition metal phosphides using machine learning M. Yan et al. https://doi.org/10.1016/j.mcat.2023.113402
656. Low-Temperature Prediction in Commercial Lithium-Ion Batteries during Dynamic Usage via Enhanced Physics-Informed Neural Networks E. Pereira & D. Soares https://doi.org/10.1021/acsomega.5c11152
657. Implications of Construction 4.0 technologies to enhancing well-being: a fuzzy TOPSIS evaluation H. Shafei et al. https://doi.org/10.1108/CI-08-2023-0213
658. Simulation of East Asian Summer Monsoon (EASM) in SP‐CCSM4: Part I—Seasonal mean state and intraseasonal variability Y. Jin & C. Stan https://doi.org/10.1002/2015JD024035
659. Prediction of flow-induced local scour depth at the uniform bridge pier using masked attention neural network B. Lu et al. https://doi.org/10.1016/j.oceaneng.2022.113018
660. Evaluating Satellite-Based Water Quality Sensing of Inland Waters on Basis of 100+ German Water Bodies Using 2 Different Processing Chains S. Schmidt et al. https://doi.org/10.3390/rs16183416
661. ResiDualNet: A novel electric vehicle charging data imputation technique to enhance load forecasting accuracy B. Fahim et al. https://doi.org/10.1007/s12273-025-1236-8
662. A thermo-mechanical-chemical coupled failure model for turbine blade coatings within a phase-field framework X. Cai et al. https://doi.org/10.1016/j.engfracmech.2026.112146
663. Estimation of water quality in coastal aquaculture waters using the combination of machine learning and unmanned aerial vehicle multispectral imagery W. Li et al. https://doi.org/10.1016/j.aquaculture.2025.743002
664. Physics-guided residual learning for phase-aware UAV trajectory prediction in urban environments M. Islam et al. https://doi.org/10.1038/s41598-026-67222-5
665. Spray Drift Generated in Vineyard during Under-Row Weed Control and Suckering: Evaluation of Direct and Indirect Drift-Reducing Techniques M. Grella et al. https://doi.org/10.3390/su12125068
666. Selective Alkaline Leaching of Mechanochemically Activated Spent LiCoO2 Cathodes: Taguchi Optimization and Machine-Learning-Assisted Interpretation L. Mussapyrova et al. https://doi.org/10.3390/met16101081
667. Evaluation of suspended particulate matter retrieval models for subtropical estuarine waters monitoring R. Zem et al. https://doi.org/10.1080/01431161.2026.2677906
668. Leveraging Ensemble and Hybrid Forecasting Tools to Increase Accuracy: Turkey COVID-19 Case Study O. Evkaya et al. https://doi.org/10.1007/s42979-025-03658-2
669. Causal machine learning models for predicting low birth weight in midwife-led continuity care intervention in North Shoa Zone, Ethiopia W. Moges et al. https://doi.org/10.1186/s12911-025-02917-9
670. A data-driven framework for predicting mechanical properties of coal–rock composites in deep mining Q. Ou et al. https://doi.org/10.1007/s11600-026-01946-w
671. Reconstructing missing hourly real-time precipitation data using a novel intermittent sliding window period technique for automatic weather station data N. Hema & K. Kant https://doi.org/10.1007/s13351-017-6084-8
672. Predicting Therapy Success and Costs for Personalized Treatment Recommendations Using Baseline Characteristics: Data-Driven Analysis V. Bremer et al. https://doi.org/10.2196/10275
673. Probabilistic forecasting of short-term electricity prices in the Turkish day-ahead market K. Akpınar https://doi.org/10.35860/iarej.1820591
674. Statistical reconstruction of daily temperature and sea level pressure in Europe for the severe winter 1788/89 D. Pappert et al. https://doi.org/10.5194/cp-18-2545-2022
675. Response surface prediction model of radon exhalation rate on beach surface of uranium tailings pond based on single factor law Y. Chen et al. https://doi.org/10.1007/s10967-024-09687-0
676. End-to-end framework for panoramic indoor style transfer: From photorealistic generation to immersive WebXR exploration M. Tukur et al. https://doi.org/10.1016/j.imavis.2026.106182
677. Issues in assessing analytical performance specifications in healthcare systems assembling multiple laboratories and measuring systems E. Theodorsson https://doi.org/10.1515/cclm-2023-1208
678. WUTrans: Whole-spectrum unilateral-query-secured transformer for 4D CBCT reconstruction P. Yuan et al. https://doi.org/10.1016/j.bspc.2024.107197
679. Improved proportional-integral voltage controller for a piezoelectric energy harvesting system converter utilizing lightning search algorithm M. Sarker et al. https://doi.org/10.1080/00150193.2017.1359028
680. Toward FOXM1 inhibitors based on supervised machine learning classification models and similarity-based screening A. Kharwar et al. https://doi.org/10.1007/s10822-026-00952-w
681. Modelling Sectoral Energy Consumption in Malaysia: Assessing the Asymmetric Effects C. Tang et al. https://doi.org/10.3390/su14031816
682. Company Values of Malaysian Listed Companies' Sustainability for Palm Oil Industry: Financial Panel Data Model Approach A. Khin et al. https://doi.org/10.35609/afr.2022.6.4(1)
683. Correlations between Web Searches and COVID-19 Epidemiological Indicators in Brazil M. Locatelli et al. https://doi.org/10.1590/1678-4324-2022210648
684. An Effective Temperature Profile Prediction in Additive Manufacturing Process Using Fractional GNU Global Herding Optimization-based Deep Learning Technique S. Ahmed et al. https://doi.org/10.1007/s12008-023-01349-x
685. Modelling on Impact of Building Obstruction for V2I Communication Link in Micro Cellular Environment J. Turner et al. https://doi.org/10.1088/1742-6596/1755/1/012031
686. Deep multi-view information-powered vessel traffic flow prediction for intelligent transportation management H. Li et al. https://doi.org/10.1016/j.tre.2025.104072
687. Performance Analysis of Phase Change Material Walls and Different Window-to-Wall Ratios in Elderly Care Home Buildings Under Hot-Summer and Cold-Winter Climate W. Chen et al. https://doi.org/10.3390/buildings16020367
688. The imputation of missingness in cyclic and non-cyclic Electromyography(EMG) signaling data F. Sarasir & V. Purutcuoglu https://doi.org/10.15672/hujms.1689242
689. Extreme rainfall, rainfall erosivity, and hillslope erosion in Australian Alpine region and their future changes Q. Zhu et al. https://doi.org/10.1002/joc.6266
690. Predicting CO2 emissions using UAV spectral and thermal data in urban lawns: A case study of buffalograss and St. Augustinegrass J. Iradukunda et al. https://doi.org/10.1016/j.ufug.2026.129297
691. The overreliance on statistical goodness-of-fit and under-reliance on model validation in discrete choice models: A review of validation practices in the transportation academic literature G. Parady et al. https://doi.org/10.1016/j.jocm.2020.100257
692. Investigating the Impact of Spatiotemporal Variations in Water Surface Optical Properties on Satellite-Derived Bathymetry Estimates in the Eastern Mediterranean F. Muhammad et al. https://doi.org/10.3390/rs17030444
693. A case study of tunnel boring machines advance rate prediction using meta-heuristic techniques S. Jahanmiri et al. https://doi.org/10.1007/s12517-024-11979-4
694. ST-ResGAT: explainable spatio-temporal graph neural network for road condition prediction and priority-driven maintenance M. Topu et al. https://doi.org/10.1093/iti/liag006
695. Flow characteristics and advanced forecasting method for ventilated cavitating flow around an axisymmetric body with different ventilation modes K. Chen et al. https://doi.org/10.1063/5.0284354
696. Concrete Strength Prediction Using Different Machine Learning Processes: Effect of Slag, Fly Ash and Superplasticizer C. Qi et al. https://doi.org/10.3390/ma15155369
697. Distributed robust Gaussian Process regression S. Mair & U. Brefeld https://doi.org/10.1007/s10115-017-1084-7
698. The Use of Machine Learning for Inferencing the Effectiveness of a Rehabilitation Program for Orthopedic and Neurological Patients V. Santilli et al. https://doi.org/10.3390/ijerph20085575
699. Efficient Bayesian model updating with surrogate model of a high-rise building based on MCMC and ambient data F. Zhang et al. https://doi.org/10.1016/j.engstruct.2025.120656
700. Deep Learning Framework for Freeway Speed Prediction in Adverse Weather A. Shabarek et al. https://doi.org/10.1177/0361198120947421
701. Optuna Tabanlı Hiper Parametre Optimizasyonu ile Konut Fiyat Tahminlemede Makine Öğrenmesi Tekniklerinin Karşılaştırmalı Analizi V. Sinap https://doi.org/10.29109/gujsc.1544987
702. Impact of economic development on CO2 emission in Africa; the role of BEVs and hydrogen production in renewable energy integration O. Bamisile et al. https://doi.org/10.1016/j.ijhydene.2020.10.134
703. Spatiotemporal patterns and regional differences of lake ice phenology across mainland China Y. Kuluwan et al. https://doi.org/10.1007/s10584-026-04245-x
704. Hybrid Artificial Intelligence Approaches for Predicting Buckling Damage of Steel Columns Under Axial Compression L. Le et al. https://doi.org/10.3390/ma12101670
705. Adaptive LASSO estimation for functional hidden dynamic geostatistical models P. Maranzano et al. https://doi.org/10.1007/s00477-023-02466-5
706. Enhancing the Usability of In-Situ Marine Observations Under Increasing Uncertainty of Satellite Data: A Spatiotemporal Interpolation Approach for Korean Offshore and Coastal Waters Y. Yu et al. https://doi.org/10.3390/jmse14040343
707. Ensemble SVM for characterisation of crude oil viscosity M. Oloso et al. https://doi.org/10.1007/s13202-017-0355-x
708. Neural predictors of motor control and impact of visuo‐proprioceptive information in youth S. Corporaal et al. https://doi.org/10.1002/hbm.23754
709. Density of photonic states in aperiodic structures V. Chistyakov et al. https://doi.org/10.1103/PhysRevB.107.014205
710. Within and among farm variability of coffee quality of smallholders in southwest Ethiopia M. Getachew et al. https://doi.org/10.1007/s10457-023-00833-3
711. Harmonics Forecasting of Renewable Energy System Using Hybrid Model Based on LSTM and ANFIS F. Hadi & H. Aly https://doi.org/10.1109/ACCESS.2024.3386092
712. Novel static analysis of a rotary sinter cooling process for determination of temperature distribution and waste heat recovery potential to generate power with ORC G. Yuksel et al. https://doi.org/10.1007/s00231-026-03738-w
713. Effects of local time on the variations of the total electron contents at an American and Asian longitudes and their comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 models during solar cycle 24 Y. Kayode et al. https://doi.org/10.1016/j.jastp.2024.106271
714. Prediction of Foliar Nutrient Contents and Differentiation of Scion/Rootstock Combinations in Citrus via X-Ray Fluorescence Spectrometry M. Rossi et al. https://doi.org/10.3390/agriengineering7030079
715. A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines F. Lasheras et al. https://doi.org/10.3390/s150307062
716. Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus C. Faverjon et al. https://doi.org/10.1089/vbz.2015.1883
717. A deep neural network based battery state of charge: electric vehicle application R. Jebahi et al. https://doi.org/10.1007/s11581-025-06440-9
718. Uphill resampling for particle filter and its implementation on graphics processing unit Ö. Dülger et al. https://doi.org/10.1016/j.parco.2022.102994
719. Mapping the spatio-temporal distribution of burned areas in the Amazon from 2001 to 2020: an ensemble modeling approach M. Abid et al. https://doi.org/10.1007/s10651-025-00661-x
720. A Novel Hybrid Model for Predicting Blast-Induced Ground Vibration Based on k-Nearest Neighbors and Particle Swarm Optimization X. Bui et al. https://doi.org/10.1038/s41598-019-50262-5
721. Advanced detection methods and machine learning analysis of temporal and spatial patterns of equatorial plasma bubble depth I. Adawa et al. https://doi.org/10.1016/j.jastp.2025.106495
722. Landslide susceptible areas identification using IDW and Ordinary Kriging interpolation techniques from hard soil depth at middle western Central Java, Indonesia . Yanto et al. https://doi.org/10.1007/s11069-021-04982-5
723. Insights into the key structural features of N1-ary-benzimidazols as HIV-1 NNRTIs using molecular docking, molecular dynamics, 3D-QSAR, and pharmacophore modeling W. Wang et al. https://doi.org/10.1007/s11224-018-1204-3
724. Bias evaluation and minimization for estuarine total dissolved solids (TDS) patterns constructed using spatial interpolation techniques N. Ndou & N. Nontongana https://doi.org/10.1016/j.marpolbul.2024.117353
725. AttentionTTE: a deep learning model for estimated time of arrival M. Li et al. https://doi.org/10.3389/frai.2024.1258086
726. A validation study of the Stoyanova et al. method (2017) for age-at-death estimation quantifying the 3D pubic symphyseal surface of adult males of European populations A. Kotěrová et al. https://doi.org/10.1007/s00414-018-1934-1
727. A new approach for estimating spatial-temporal phreatic evapotranspiration at a regional scale using NDVI and water table depth measurements T. Zhao et al. https://doi.org/10.1016/j.agwat.2022.107500
728. Merging Data with Modeling: An Example from Fatigue D. Harlow https://doi.org/10.3390/ma17143383
729. Evaluating satellite and reanalysis rainfall products for extreme events in Rio de Janeiro State, Brazil P. de Bodas Terassi et al. https://doi.org/10.1016/j.pce.2026.104600
730. Infant mortality rates in Ghana: progress toward sustainable development goal 3 S. Opoku et al. https://doi.org/10.1186/s12889-025-25576-x
731. Estimation and Prediction of the Polymers’ Physical Characteristics Using the Machine Learning Models I. Malashin et al. https://doi.org/10.3390/polym16010115
732. YOLO-light-pruned: A lightweight model for monitoring maize seedling count and leaf age using near-ground and UAV RGB images T. Jiang et al. https://doi.org/10.1016/j.aiia.2025.10.002
733. General model for service life analysis of reinforced concrete structures subject to chloride penetration C. Balestra et al. https://doi.org/10.1016/j.conbuildmat.2021.124727
734. Data-driven planning of reliable itineraries in multi-modal transit networks M. Redmond et al. https://doi.org/10.1007/s12469-019-00221-0
735. Sensitivity Analysis of Calibration Methods and Factors Effecting the Statistical Nature of Radiation Measurement K. Kumari & M. Goswami https://doi.org/10.1007/s11265-021-01685-9
736. GeoRF: Geometric Constrained RaDAR Fields W. Sheng et al. https://doi.org/10.1109/ACCESS.2025.3563135
737. Fuzzy Windows with Gaussian Processed Labels for Ordinal Image Scoring Tasks C. Kang et al. https://doi.org/10.3390/app13064019
738. Shedding Light on the Black Box: Integrating Prediction Models and Explainability Using Explainable Machine Learning Y. Zhang et al. https://doi.org/10.1177/10944281251323248
739. Investigation of ANN Architecture for Predicting Load‐Carrying Capacity of Castellated Steel Beams T. Nguyen et al. https://doi.org/10.1155/2021/6697923
740. LSTM and Transformer-based framework for bias correction of ERA5 hourly wind speeds F. Houndekindo & T. Ouarda https://doi.org/10.1016/j.energy.2025.136498
741. Enhancing trading strategies by combining incremental reinforcement learning and self-supervised prediction C. Zhou et al. https://doi.org/10.1016/j.eswa.2025.128297
742. The Effect of Provincial Policies on the COVID-19 Mortality Rate: Risk Analysis Study in Hamadan Province R. Ahmaddoost-rozdari et al. https://doi.org/10.52547/ismj.25.4.340
743. Beyond immediate relief: Investigating multi-faceted water management in inter-basin water transfer projects O. Ghadirian Baharanchi et al. https://doi.org/10.1016/j.jclepro.2024.143243
744. Species richness and evenness of European bird communities show differentiated responses to measures of productivity L. Sandal et al. https://doi.org/10.1111/1365-2656.14136
745. Machine learning approaches for groundwater temperature prediction in Austria: Impacts of hydro-climatic variability, feature engineering, and model complexity A. Sobhani et al. https://doi.org/10.1016/j.ejrh.2025.102987
746. A machine-learning-based composition design of ternary Cu-based Rochow-Müller catalyst with high M2 selectivity T. Ma et al. https://doi.org/10.1016/j.apcata.2024.119592
747. Assessing the Impact of Multi-Decadal Land Use Change on Agricultural Water–Energy Dynamics in the Awash Basin, Ethiopia: Insights from Remote Sensing and Hydrological Modeling T. Gemechu et al. https://doi.org/10.3390/agronomy15122804
748. A robust trust inference algorithm in weighted signed social networks based on collaborative filtering and agreement as a similarity metric K. Akilal et al. https://doi.org/10.1016/j.jnca.2018.11.008
749. A comparison of two metamodeling techniques for analog ICs: contemporary Kriging metamodels vs. classical RSMs H. Hamad et al. https://doi.org/10.1007/s12046-021-01615-2
750. ENHANCING TOMATO VARIETY SELECTION AND YIELD PREDICTION MODEL USING ADVANCED MACHINE LEARNING TECHNIQUES U. R. & N. Selvakumari https://doi.org/10.29121/shodhkosh.v5.i6.2024.2371
751. Automated software debugging and bug prediction through the use of machine learning and deep learning A. Abdin et al. https://doi.org/10.1007/s11227-026-08776-z
752. Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS D. Tien Bui et al. https://doi.org/10.1016/j.jhydrol.2016.06.027
753. DGPIR: Degradation-Guided Prompting for All-in-One Radiometric Restoration of Level-1 Optical Satellite Imagery K. Zhou et al. https://doi.org/10.1109/TGRS.2026.3716720
754. Nonlinear Mixed Effect Model Used in a Simulation of the Impact of Climate Change on Height Growth of Cyclobalanopsis glauca H. Duan & G. Zhang https://doi.org/10.3390/f13030463
755. A Novel Method of Design Flood Hydrographs Estimation for Flood Hazard Mapping W. Gądek et al. https://doi.org/10.3390/w14121856
756. Enhancing forecasting accuracy in dynamic environments via PELT-driven drift detection and model adaptation N. Pawar et al. https://doi.org/10.1016/j.nxener.2025.100462
757. Development of optimized ensemble machine learning-based prediction models for wire electrical discharge machining processes B. Sarker et al. https://doi.org/10.1038/s41598-024-74291-x
758. Development of a kiln petcoke mill predictive model based on a multi-regression XGBoost algorithm M. Benchekroun et al. https://doi.org/10.1007/s00170-023-12689-z
759. Comparison of Precipitation Rates from Global Datasets for the Five-Year Period from 2019 to 2023 H. Hartmann https://doi.org/10.3390/hydrology12010004
760. VMD-ConvTSMixer: Spatiotemporal channel mixing model for non-stationary time series forecasting Y. Zhang et al. https://doi.org/10.1016/j.eswa.2025.126535
761. Using a deep convolutional network to predict the longitudinal dispersion coefficient B. Ghiasi et al. https://doi.org/10.1016/j.jconhyd.2021.103798
762. The role of biometric identification on the quality of life of older adults S. Fenuku et al. https://doi.org/10.1386/tmsd_00078_1
763. A Quantum Lightning Search Algorithm-Based Fuzzy Speed Controller for Induction Motor Drive M. Hannan et al. https://doi.org/10.1109/ACCESS.2017.2778081
764. Periodicity-aware similarity-weighted linear interpolation for missing-sample reconstruction in environmental sensor time series S. Somnugpong https://doi.org/10.1016/j.array.2026.101064
765. Multi-step ahead forecasting of regional air quality using spatial-temporal deep neural networks: A case study of Huaihai Economic Zone K. Zhang et al. https://doi.org/10.1016/j.jclepro.2020.123231
766. Evaluation of multiple satellite rainfall products over the rugged topography of the Tekeze-Atbara basin in Ethiopia T. Gebremicael et al. https://doi.org/10.1080/01431161.2018.1562585
767. Novel approach to predicting blast-induced ground vibration using Gaussian process regression C. Arthur et al. https://doi.org/10.1007/s00366-018-0686-3
768. Assessing seasonal land surface temperature patterns and environmental controls in Lao PDR using google earth engine and machine learning B. Thien et al. https://doi.org/10.1007/s10668-026-08220-5
769. New Approach for Sediment Yield Forecasting with a Two-Phase Feedforward Neuron Network-Particle Swarm Optimization Model Integrated with the Gravitational Search Algorithm S. Meshram et al. https://doi.org/10.1007/s11269-019-02265-0
770. A metrological foundation for absolute transcriptomics using International System of Units-anchored calibrators Y. Zhang et al. https://doi.org/10.1038/s41467-026-70582-1
771. Enhancing Automated Scoring of Math Self-Explanation Quality Using LLM-Generated Datasets: A Semi-Supervised Approach R. Nakamoto et al. https://doi.org/10.3390/computers12110217
772. Exploring the use of astronomical seasons in municipal solid waste disposal rates modeling K. Adusei et al. https://doi.org/10.1016/j.scs.2022.104115
773. Climate model evaluation studies in Ethiopia: a systematic review D. Olana & D. Gemeda https://doi.org/10.1007/s00704-025-05588-8
774. Precision fertilization method of field crops based on the Wavelet-BP neural network in China Y. Dong et al. https://doi.org/10.1016/j.jclepro.2019.118735
775. Data-driven gait model for bipedal locomotion over continuous changing speeds and inclines B. Singh et al. https://doi.org/10.1007/s10514-023-10108-6
776. Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh Z. Yaseen et al. https://doi.org/10.1038/s41598-021-82977-9
777. Assessment of future hydrometeorological variability in the Konya Basin, Türkiye using bias-corrected CMIP6 projections O. Katipoğlu et al. https://doi.org/10.1016/j.jastp.2026.106885
778. A physics-guided permeability prediction equation for digital rocks based on pore network structural parameters S. Mahayi et al. https://doi.org/10.1063/5.0348331
779. Mapping Soil Salinity in Arid Agricultural Regions Using Multi-Source Remote Sensing and a Long-Range Dependency-Enhanced Deep Learning Framework M. Qian et al. https://doi.org/10.3390/land15101966
780. High-resolution 3D hydrodynamic modeling and comprehensive assessment of tidal current energy resources T. Zou et al. https://doi.org/10.1016/j.oceaneng.2024.119514
781. Predicting elections from social media: a three-country, three-method comparative study K. Jaidka et al. https://doi.org/10.1080/01292986.2018.1453849
782. First QSTR Report on Allium Cepa Phytotoxicity of Pesticides A. Murmu et al. https://doi.org/10.4018/IJQSPR.290009
783. Prediction of shield machine posture using the GRU algorithm with adaptive boosting: A case study of Chengdu Subway project H. Xiao et al. https://doi.org/10.1016/j.trgeo.2022.100837
784. Method for indirect determination of soil parameters for numerical simulation of dikes and earth dams T. Fichtner et al. https://doi.org/10.1007/s13201-022-01766-5
785. Comparison between genetic algorithm‐multiple linear regression and back‐propagation‐artificial neural network methods for predicting the LD50 of organo (phosphate and thiophosphate) compounds M. Kianpour et al. https://doi.org/10.1002/jccs.201900514
786. Predicting short‐term mobile Internet traffic from Internet activity using recurrent neural networks G. Santos et al. https://doi.org/10.1002/nem.2191
787. Modelling Spatio-Temporal Variation in Sparse Rainfall Data Using a Hierarchical Bayesian Regression Model S. Mukhopadhyay et al. https://doi.org/10.1007/s13253-019-00357-3
788. Performance evaluation of satellite precipitation estimation with ground monitoring stations over southern Himalayas in Bhutan K. Adhikari et al. https://doi.org/10.1007/s11600-020-00434-z
789. Stress Distribution Analysis on Hyperspectral Corn Leaf Images for Improved Phenotyping Quality D. Ma et al. https://doi.org/10.3390/s20133659
790. Climate and Vegetation Dominate Lake Eutrophication in the Inner Mongolia–Xinjiang Plateau (2000–2024) Y. Zhang et al. https://doi.org/10.3390/rs18070988
791. Building Auto-Encoder Intrusion Detection System based on random forest feature selection X. Li et al. https://doi.org/10.1016/j.cose.2020.101851
792. Using UAV Images and Phenotypic Traits to Predict Potato Morphology and Yield in Peru D. Ccopi et al. https://doi.org/10.3390/agriculture14111876
793. Geometric Evaluation of an Oscillating Water Column Wave Energy Converter Device Using Representative Regular Waves of the Sea State Found in Tramandaí, Brazil A. Mocellin et al. https://doi.org/10.3390/pr12112352
794. Análisis de frecuencias de crecientes bivariado de fechas de ocurrencia y gasto máximo a través de funciones Cópula D. Campos-Aranda https://doi.org/10.24850/j-tyca-2024-04-03
795. Prediction of binding energy using machine learning approach B. Pandey et al. https://doi.org/10.1063/5.0230425
796. Development and Evaluation of Hybrid Artificial Neural Network Architectures for Modeling Spatio-Temporal Groundwater Fluctuations in a Complex Aquifer System T. Roshni et al. https://doi.org/10.1007/s11269-019-02253-4
797. Comprehensive spatio-temporal analysis of ambient air quality of Kolkata Municipal Corporation, Kolkata (West Bengal, India) during 2017–2020 G. Bhunia et al. https://doi.org/10.1007/s12517-022-11081-7
798. Automatic Modeling for Concrete Compressive Strength Prediction Using Auto-Sklearn M. Shi & W. Shen https://doi.org/10.3390/buildings12091406
799. Big Data Analytics in Healthcare H. Asri et al. https://doi.org/10.4018/IJDST.2019100104
800. Ensemble Algorithm for Simulated Corrosion Data-tentative C. Yinka-Banjo et al. https://doi.org/10.2478/ast-2023-0015
801. Future high- and low-flow estimations for Central Vietnam: a hydro-meteorological modelling chain approach Q. Dang et al. https://doi.org/10.1080/02626667.2017.1353696
802. A comprehensive multi-objective framework for the estimation of crash frequency models Z. Ahern et al. https://doi.org/10.1016/j.aap.2024.107844
803. Estimation of Daily Solar Radiation Budget at Kilometer Resolution over the Tibetan Plateau by Integrating MODIS Data Products and a DEM L. Roupioz et al. https://doi.org/10.3390/rs8060504
804. Deforestation probability assessment using integrated machine learning algorithms of Eastern Himalayan foothills (India) S. Saha et al. https://doi.org/10.1016/j.rcradv.2022.200077
805. Autopilot control unmanned aerial vehicle system for sewage defect detection using deep learning B. Pandey et al. https://doi.org/10.1002/eng2.12852
806. Impact of Milk pH and Fat Content on the Prediction of Milk-to-Plasma Ratio: Knowledge Gap and Considerations for Lactation Study Design and Interpretation K. Abduljalil & M. Faisal https://doi.org/10.1007/s40262-024-01432-w
807. Artificial Intelligence Optimization for User Prediction and Efficient Energy Distribution in Electric Vehicle Smart Charging Systems S. Shern et al. https://doi.org/10.3390/en17225772
808. Mechanistically mapping near-surface temperature in the understory of temperate forests: A validation of the microclima R package against empirical observations T. Brusse et al. https://doi.org/10.1016/j.agrformet.2024.109894
809. The Extended Goodwin Model and Wage–Labor Paradoxes Metric in South Africa T. Chikore et al. https://doi.org/10.3390/mca30050098
810. IR-Based Sleep Monitoring: Movement, Respiration, and Sleep Staging With a Structure-Aware Cross-Modal EEG Knowledge Distillation Z. Yu et al. https://doi.org/10.1109/JIOT.2025.3583049
811. Transfer learning with graph neural networks to predict polymer solubility parameters R. Fang et al. https://doi.org/10.1038/s41524-026-02109-7
812. Exploring atmospheric stagnation during a severe particulate matter air pollution episode over complex terrain in Santiago, Chile R. Toro A et al. https://doi.org/10.1016/j.envpol.2018.10.067
813. Unveiling the interspecies correlation and sensitivity factor analysis of rat and mouse acute oral toxicity of antimicrobial agents: first QSTR and QTTR Modeling report P. Banjare et al. https://doi.org/10.1093/toxres/tfae191
814. Advanced financial risk forecasting using enhanced kernel-based extreme learning machines: Tackling challenges in bankruptcy problem S. Ye et al. https://doi.org/10.1016/j.asej.2025.103518
815. Hybrid Artificial Intelligence Approaches for Predicting Critical Buckling Load of Structural Members under Compression Considering the Influence of Initial Geometric Imperfections H. Ly et al. https://doi.org/10.3390/app9112258
816. A hybrid fuzzy logic/genetic algorithm model based on experimental data for estimation of cuttings concentration during drilling D. Chowdhury & S. Hovda https://doi.org/10.1016/j.geoen.2023.212387
817. Tourism stock price and COVID-19: medium-term relationship with passenger transport, hotel, and tour operator subsectors I. Carrillo-Hidalgo et al. https://doi.org/10.1080/13683500.2022.2142536
818. Evapotranspiration of winter wheat estimated with the FAO 56 approach and NDVI measurements in a temperate humid climate of NW Europe P. Drerup et al. https://doi.org/10.1016/j.agwat.2017.07.010
819. Impact of Interpolation Method and Location on Nonlinear Analysis of RR Intervals K. Amano et al. https://doi.org/10.1541/ieejeiss.146.423
820. Shaping pre-modern digital terrain models: The former topography at Charlemagne’s canal construction site J. Schmidt et al. https://doi.org/10.1371/journal.pone.0200167
821. Implementation of Univariate Paradigm for Streamflow Simulation Using Hybrid Data-Driven Model: Case Study in Tropical Region Z. Yaseen et al. https://doi.org/10.1109/ACCESS.2019.2920916
822. Perakende Sektöründe Makine Öğrenmesi Algoritmalarının Karşılaştırmalı Performans Analizi: Black Friday Satış Tahminlemesi V. Sinap https://doi.org/10.29249/selcuksbmyd.1401822
823. Thermal Power Plant Pollution Monitoring and Control using Internet of Things M. Manoharan et al. https://doi.org/10.1088/1757-899X/1295/1/012011
824. Feed-forward neural networks for genomic selection: insights into varying levels of dominance heritability H. Sahebalam & M. Gholizadeh https://doi.org/10.1186/s12864-026-12807-7
825. A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea K. Nam et al. https://doi.org/10.1016/j.rser.2020.109725
826. H-ConvLSTM to Estimate Reference Evapotranspiration From Air Temperature and Relative Humidity A. Haris et al. https://doi.org/10.1109/ACCESS.2025.3585771
827. Multi-agent generative AI for concept evaluation: consistency, knowledge integration and human alignment . Mas’udah et al. https://doi.org/10.1017/pds.2026.10603
828. Dynamic Prediction of Shale Gas Drilling Costs Based on Machine Learning T. Yang et al. https://doi.org/10.3390/app142310984
829. Transitioning operational satellite grassland curing from MODIS to VIIRS D. Wright & L. Majewski https://doi.org/10.1071/WF22227
830. Meta-learning–driven adaptive optimisation of building-integrated photovoltaic envelopes T. Samarasinghalage et al. https://doi.org/10.1016/j.enbuild.2026.117782
831. On the use of surrogate models for the production planning of biofuels via hydro-processed esters and fatty acids (HEFA) process G. Gallardo et al. https://doi.org/10.1016/j.compchemeng.2026.109649
832. Quantification of Root-Knot Nematode Infestation in Tomato Using Digital Image Analysis T. Pun et al. https://doi.org/10.3390/agronomy11122372
833. Construction of Prediction Models of Mass Ablation Rate for Silicone Rubber-Based Flexible Ablative Composites Based on a Small Dataset W. Chen et al. https://doi.org/10.3390/app14178007
834. Remaining-capacity estimation of lithium-ion batteries using heatmap-based denoising autoencoder and vision transformer algorithm Y. Jang & J. Park https://doi.org/10.1007/s43236-025-01134-x
835. Fusion of Optical and SAR Imagery for Crop Area Estimation: A Case Study of Wheat and Mustard in Semi-arid India R. Saravanakumar et al. https://doi.org/10.1007/s12524-026-02426-w
836. Comparing different methods for statistical modeling of particulate matter in Tehran, Iran V. Mehdipour et al. https://doi.org/10.1007/s11869-018-0615-z
837. How to determine when data incompleteness compromises the correct training of data-enhanced mechanical models of haemodialysis? A data quality criterion L. Pizzi et al. https://doi.org/10.1016/j.jbi.2026.105058
838. Enhanced deep learning approach for improved maximum temperature forecasting: a case study in the Sahara region, Morocco M. Licer et al. https://doi.org/10.1007/s00704-024-05320-y
839. A Sales Forecasting Model for New-Released and Short-Term Product: A Case Study of Mobile Phones S. Hwang et al. https://doi.org/10.3390/electronics12153256
840. A hierarchical interaction message net for accurate molecular property prediction H. Hong et al. https://doi.org/10.1038/s42004-026-01922-x
841. Prediction of the Adsorption Behaviors of Radionuclides onto Bentonites Using a Machine Learning Method D. Kim & J. Lee https://doi.org/10.3390/min12101207
842. Comparison of different reliability estimation methods for single-item assessment: a simulation study S. Zhang & K. Colvin https://doi.org/10.3389/fpsyg.2024.1482016
843. Multi-Modal Cross Learning for an FMCW Radar Assisted by Thermal and RGB Cameras to Monitor Gestures and Cooking Processes M. Altmann et al. https://doi.org/10.1109/ACCESS.2021.3056878
844. Countering Negative Effects of Terrain Slope on Airborne Laser Scanner Data Using Procrustean Transformation and Histogram Matching E. Hansen et al. https://doi.org/10.3390/f8100401
845. Year-ahead Ambient Temperature Forecasting in Pharmaceutical Transport Lanes Thermal Conditions A. van den Berg et al. https://doi.org/10.1016/j.procs.2022.03.035
846. Development of water consumption prediction models: a data-driven machine learning and deep learning approach M. Bathre https://doi.org/10.1080/13241583.2026.2708368
847. Comprehensive evaluation of machine learning models for suspended sediment load inflow prediction in a reservoir M. Idrees et al. https://doi.org/10.1007/s00477-021-01982-6
848. Assessment of solar radiation resource from the NASA-POWER reanalysis products for tropical climates in Ghana towards clean energy application A. Quansah et al. https://doi.org/10.1038/s41598-022-14126-9
849. Machine Learning Methods in Student Mental Health Research: An Ethics-Centered Systematic Literature Review M. Drira et al. https://doi.org/10.3390/app142411738
850. Explainable machine learning analysis of urban heat island in Türkiye: SHAP-based meteorological threshold assessment (1965–2024) E. Birinci et al. https://doi.org/10.1016/j.uclim.2026.102924
851. Dual-polarized quantitative precipitation estimation as a function of range M. Simpson & N. Fox https://doi.org/10.5194/hess-22-3375-2018
852. A Comparative Study of Sentinel-1 and Sentinel-2 Imagery for Riverbank Extraction in Ho Chi Minh City N. Vu & N. Huyen https://doi.org/10.1088/1755-1315/1633/1/012008
853. Differential performance of statistical versus machine learning methods in partial volume correction in oncologic F18-FDG PET/CT scanning H. Metwally et al. https://doi.org/10.1007/s12149-026-02255-4
854. Long-term wind power forecasting with series decomposition and spatio-temporal graph neural network Y. Yang et al. https://doi.org/10.1080/15435075.2024.2382351
855. A generic optimization and learning framework for Parkinson disease via speech and handwritten records N. Yousif et al. https://doi.org/10.1007/s12652-022-04342-6
856. Predicting the spatial distribution of stable isotopes in precipitation using a machine learning approach: a comparative assessment of random forest variants D. Erdélyi et al. https://doi.org/10.1007/s13137-023-00224-x
857. Groundwater level dynamics in a subtropical fan delta region and its future prediction using machine learning tools: Sustainable groundwater restoration S. Mahammad et al. https://doi.org/10.1016/j.ejrh.2023.101385
858. TD‐DFT benchmark for UV‐Vis spectra of coumarin derivatives M. Van Bay et al. https://doi.org/10.1002/vjch.202000200
859. Predictive model for growth of Clostridium perfringens during cooling of cooked pork supplemented with sodium chloride and sodium pyrophosphate V. Juneja et al. https://doi.org/10.1016/j.meatsci.2021.108557
860. Ocean Color Analytical Model Explicitly Dependent on the Volume Scattering Function M. Twardowski & A. Tonizzo https://doi.org/10.3390/app8122684
861. GAGIN: generative adversarial guider imputation network for missing data W. Wang et al. https://doi.org/10.1007/s00521-021-06862-2
862. Enhanced saturated hydraulic conductivity estimation in fine-grained soils: a voting regressor ensemble framework H. Zhang et al. https://doi.org/10.1016/j.jhydrol.2026.135041
863. Full Spectrum Raman Spectroscopy Combined With Deep Learning for Prediction of Tensile Mechanical Properties of Human Cortical Bone M. Varli et al. https://doi.org/10.1002/jbio.70371
864. Conventional Log-Based Formation Element Prediction for Reservoir Characterization in the Jimusar Shale Oil Reservoir Using a Stacked Ensemble Learning Workflow X. Xie et al. https://doi.org/10.3390/app16115234
865. Interpretable machine learning for conductivity prediction and structural generalization of imidazolium-based ionic liquids Z. Zhang et al. https://doi.org/10.1016/j.ces.2026.125358
866. Fully Connected U-Net and Its Application on Reconstructing Successively Sampled Seismic Data S. Li et al. https://doi.org/10.1109/ACCESS.2023.3271518
867. Objectively estimating the temporal evolution of accuracy and skill in a global ocean reanalysis A. Storto & S. Masina https://doi.org/10.1002/met.1609
868. Hierarchical Learning for Cognitive End-to-End Service Provisioning in Multi-Domain Autonomous Optical Networks G. Liu et al. https://doi.org/10.1109/JLT.2018.2883898
869. Integrated MASW and ERT Imaging for Geological Definition of an Unconfined Alluvial Aquifer Sustaining a Coastal Groundwater-Dependent Ecosystem in Southwest Portugal M. Paz et al. https://doi.org/10.3390/app10175905
870. Effect of supplementing L-cysteine and its group analogs on frozen semen quality of bulls: A meta-analysis S. Hayanti et al. https://doi.org/10.14202/vetworld.2022.2517-2524
871. Machine learning modeling for predicting growth dynamics of Listeria monocytogenes using ComBase database: A comprehensive feature engineering approach Z. Zhou et al. https://doi.org/10.1016/j.foodres.2026.118585
872. Response of Individual-Tree Aboveground Biomass to Spatial Effects in Pinus kesiya var. langbianensis Forests by Stand Origin and Tree Size C. Liu et al. https://doi.org/10.3390/f15020349
873. Application of Time Series Methodologies for Robust Forecasting of Atmospheric Pollutant Concentrations: PM10, SO2, NO2, NOx, and O3 in an Urban Environment O. Katipoğlu et al. https://doi.org/10.1002/tqem.70206
874. RSPCN: Super-Resolution of Digital Elevation Model Based on Recursive Sub-Pixel Convolutional Neural Networks R. Zhang et al. https://doi.org/10.3390/ijgi10080501
875. Gridded Datasets for Comparative Analysis of Rainfall Patterns Over Eco‐Climatic Zones of Narok County, Kenya O. Ombogo et al. https://doi.org/10.1155/adme/4895679
876. GSCIT: smart Hash Table-based mapping equipped genome sequence coverage inspection S. Godara et al. https://doi.org/10.1007/s10142-024-01315-0
877. Evaluation of hydrological responses to climate change in the Gibe Gojeb catchment, southwestern Ethiopia H. Kuma et al. https://doi.org/10.2166/wcc.2024.656
878. Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA Z. Yaseen et al. https://doi.org/10.1007/s11269-017-1797-0
879. Development and validation of an FT-IR method for quantitative assessment of immature fiber content in cotton samples H. Kim et al. https://doi.org/10.1177/00405175251387922
880. Prediction of Leaf Break Resistance of Green and Dry Alfalfa Leaves by Machine Learning Methods U. Ercan et al. https://doi.org/10.3390/app14041638
881. Scene-Aware Foveated Neural Radiance Fields X. Shi et al. https://doi.org/10.1109/TVCG.2024.3429416
882. Effect of the Likelihood Function on the Calibration of the Effective Manning Roughness Factor S. Cedillo et al. https://doi.org/10.3390/w16202879
883. Sequential bargaining based incentive mechanism for collaborative Internet access K. Uludağ et al. https://doi.org/10.1016/j.jnca.2020.102758
884. Adaptive heterogeneous stacking ensemble learning for predicting coal mine gas concentration Y. Xiao et al. https://doi.org/10.1016/j.aei.2026.104589
885. Automated artificial intelligence–enabled measurement of cardiac structures on point-of-care ultrasonography: a prospective multicenter validation study S. Mercaldo et al. https://doi.org/10.3389/fcvm.2026.1891962
886. A comparative analysis of super-resolution techniques for enhancing micro-CT images of carbonate rocks R. Soltanmohammadi & S. Faroughi https://doi.org/10.1016/j.acags.2023.100143
887. Flood Susceptibility Mapping Using Novel Hybrid Approach of Neural Network with Genetic Quantum Ensembles H. Cui et al. https://doi.org/10.1007/s12205-022-0559-6
888. Accelerating fluid flow simulations through doubly porous media using a FEM-assisted machine learning approach H. Ly & T. Nguyen https://doi.org/10.1016/j.rinp.2023.107036
889. Multi-rate principal component regression model for soft sensor application in industrial processes L. Zhou et al. https://doi.org/10.1007/s11432-018-9624-8
890. Full Life-Cycle Evolution and Prediction of Surface Deformation in Old Goafs of Strip Pillar Mining Areas Revealed by Long-Term SBAS-InSAR W. Zheng et al. https://doi.org/10.3390/rs18111859
891. Data Mining Paths for Standard Weekly Training Load in Sub-Elite Young Football Players: A Machine Learning Approach J. Teixeira et al. https://doi.org/10.3390/jfmk9030114
892. A new GIS-based technique using an adaptive neuro-fuzzy inference system for land subsidence susceptibility mapping O. Ghorbanzadeh et al. https://doi.org/10.1080/14498596.2018.1505564
893. A Global-Information-Constrained Deep Learning Network for Digital Elevation Model Super-Resolution X. Han et al. https://doi.org/10.3390/rs15020305
894. A New Criterion for Model Selection H. Pham https://doi.org/10.3390/math7121215
895. Study on the Backlash Measurement and Software Compensation of Basis Weight Control Valve B. Wang et al. https://doi.org/10.7584/JKTAPPI.2017.08.49.4.16
896. Generalised Linear Models for Prediction of Dissolved Oxygen in a Waste Stabilisation Pond D. Pham et al. https://doi.org/10.3390/w12071930
897. Estimation at Completion Simulation Using the Potential of Soft Computing Models: Case Study of Construction Engineering Projects E. AlHares & C. Budayan https://doi.org/10.3390/sym11020190
898. Data Structure-Aware Ensemble Modeling for Time-Series Prediction: A Case Study of Sewage Generation J. Lee et al. https://doi.org/10.3390/app16104842
899. Prediction and validation of residual stress and deformation in a thick-walled P91 header-nozzle welded structure using an equivalent thermal-cycle method R. Xiang et al. https://doi.org/10.1016/j.ijpvp.2026.105942
900. Selection of the Value of the Power Distance Exponent for Mapping with the Inverse Distance Weighting Method—Application in Subsurface Porosity Mapping, Northern Croatia Neogene U. Barudžija et al. https://doi.org/10.3390/geosciences14060155
901. An optimized optical diffractive deep neural network with OReLU function based on genetic algorithm C. Dong et al. https://doi.org/10.1016/j.optlastec.2022.109104
902. Influence of the Ionospheric Delay on Designation of an Aircraft Position J. Cwiklak et al. https://doi.org/10.26552/com.C.2020.3.3-10
903. The interpretable descriptors for fatigue performance of wrought aluminum alloys P. Bai et al. https://doi.org/10.1016/j.jmrt.2024.08.160
904. CMIP6 multi-model ensemble projections of Boro rice irrigation requirements and scheduling under climate change in North-Western Bangladesh M. Islam et al. https://doi.org/10.1016/j.rineng.2026.111968
905. A parallel–serial echo state network with evolutionary hyper-parameter optimization for industrial time-series forecasting W. Zhou et al. https://doi.org/10.1016/j.engappai.2026.115423
906. Relationship between groundwater level variations using Grace satellite data and rainfall M. Arast et al. https://doi.org/10.1680/jwama.19.00038
907. QSAR modeling with ETA indices for cytotoxicity and enzymatic activity of diverse chemicals A. Seth et al. https://doi.org/10.1016/j.jhazmat.2020.122498
908. Prediction of compressive strength of GGBFS and Flyash-based geopolymer composite by linear regression, lasso regression, and ridge regression U. Sharma et al. https://doi.org/10.1007/s42107-023-00721-2
909. MPCID, A new high-resolution multi-precipitation concentration indicators dataset for mainland China D. Zhang et al. https://doi.org/10.1038/s41597-025-06515-2
910. Post-Fire Forest Pulse Recovery: Superiority of Generalized Additive Models (GAM) in Long-Term Landsat Time-Series Analysis N. Arij et al. https://doi.org/10.3390/s26020493
911. Artefact and risk area detection of the tanDEM-X 30m edited DEM using an integrated machine learning and dem-of-difference framework: a case study in the Alps P. Dong et al. https://doi.org/10.1080/17538947.2026.2707690
912. Physics-Informed Cascaded Learning for Predicting and Optimizing Geometry and Quality in Laser Cladding Repair of Carburized Gear Steel Y. Xu et al. https://doi.org/10.3390/ma19173793
913. Improvements and Applications in Climate Data Analysis for Determining Reference Rainfall Years C. Albright & H. Schramm https://doi.org/10.1175/JAMC-D-17-0267.1
914. Design and optimization of resveratrol-loaded porous calcium silicate powders for dissolution and photostability enhancement P. Benjasirimongkol et al. https://doi.org/10.1016/j.heliyon.2019.e01399
915. A rolling-origin ensemble forecasting framework for tourism revenue: elastic net and CatBoost – the case of Türkiye (2002–2024) İ. Budak & İ. Yayla https://doi.org/10.1108/JTF-12-2025-0414
916. No-Reference Quality Assessment of Infrared Image Colorization with Color–Spatial Features D. Sheng et al. https://doi.org/10.3390/electronics14061126
917. New hybrid multi-objective feature selection: Boruta-XGBoost T. Yousefi & Ö. Varlıklar https://doi.org/10.7717/peerj-cs.3463
918. Towards Data-Driven Vehicle Estimation for Signalised Intersections in a Partially Connected Environment R. Mohammadi & C. Roncoli https://doi.org/10.3390/s21248477
919. Optimizing the timing of management interventions against fall armyworm in African smallholder maize: Modelling the pattern of larval population emergence and development A. Lowry et al. https://doi.org/10.1016/j.cropro.2022.105966
920. Study on CO 2 concentration assimilation by integrating a multi-source satellite fusion dataset based on the WRF-Chem model W. Liu et al. https://doi.org/10.1080/01431161.2026.2612845
921. Missing data imputation using correlation coefficient and min-max normalization weighting M. Shantal et al. https://doi.org/10.3233/IDA-230140
922. Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle R. Deo et al. https://doi.org/10.1016/j.envres.2017.01.035
923. PV power prediction in a peak zone using recurrent neural networks in the absence of future meteorological information D. Lee & K. Kim https://doi.org/10.1016/j.renene.2020.12.021
924. Global evolution of inland water levels: drying-speed analysis using ICESat-2 ATL13 M. Küçükoğlu & Y. Kaya https://doi.org/10.1016/j.jhydrol.2025.134486
925. STSTFN: Spatiotemporal–Spectral Land Surface Temperature Fusion Network H. Wu et al. https://doi.org/10.1109/TGRS.2026.3729241
926. Rainfall Prediction in Palembang City Using the GRU and LSTM Methods S. Wijaya et al. https://doi.org/10.61453/jods.v2023no04
927. At-vessel mortality and health assessments reveal management priorities for chondrichthyan bycatch in trawl fisheries D. Ruiz-García et al. https://doi.org/10.1093/icesjms/fsaf228
928. Combining Machine Learning and Vis-NIR Spectroscopy to Estimate Nutrients in Fruit Tree Leaves A. Miranda Corrêa et al. https://doi.org/10.3390/horticulturae12010108
929. Rainfall–Surface Runoff Estimation Using SCS-CN Model and Geospatial Techniques: A Case Study of the Shatt Al-Arab Region, Iraq–Iran H. Allafta et al. https://doi.org/10.3390/earth7010032
930. Combination of remote sensing with crop modeling using Bayesian inferences to predict irrigated cotton yield F. Moghbel et al. https://doi.org/10.1016/j.agwat.2025.109675
931. Evaluation of the Impact of Machine Learning on the Prediction of Residential Energy Consumption R. Machaca-Casani et al. https://doi.org/10.1016/j.epsr.2025.112443
932. Translation, cross-cultural adaptation and clinimetric properties of the Brazilian Portuguese version of the Brace Questionnaire I. Fernandes et al. https://doi.org/10.1007/s43390-024-00883-2
933. BOL-LPP: A Bayesian-Optimized LSTM Model for Day-Ahead Load Price Forecasting in the ERCOT Market Y. Mohamed et al. https://doi.org/10.1109/OJCS.2025.3580107
934. Development of Regression Model for Predicting the Maximum Static Friction Force of Tractors with a Front-End Loader S. Kim et al. https://doi.org/10.1007/s42853-023-00194-w
935. Interpretable machine learning for bridge-pier scour prediction and flood resilience A. Khan & D. Ismael https://doi.org/10.3389/fbuil.2025.1731114
936. Forecasting Bitcoin Price With Neural and Statistical Models Across Different Time Granularities D. Pedroso Pereira et al. https://doi.org/10.1109/ACCESS.2025.3622921
937. Positioning Slow-Moving Platforms by UWB Technology in GPS-Challenged Areas C. Toth et al. https://doi.org/10.1061/(ASCE)SU.1943-5428.0000231
938. Prediction of Rock Strain Using Hybrid Approach of Ann and Optimization Algorithms T. Pradeep & P. Samui https://doi.org/10.1007/s10706-022-02174-x
939. Effect of polymeric fiber reinforcement on thermal gradients and physical properties in refractory castables C. Sánchez Torres et al. https://doi.org/10.1080/21870764.2026.2672837
940. The potential of hybrid evolutionary fuzzy intelligence model for suspended sediment concentration prediction O. Kisi & Z. Yaseen https://doi.org/10.1016/j.catena.2018.10.047
941. Implementation of machine learning for volcanic earthquake pattern classification using XGBoost algorithm I. Sidik et al. https://doi.org/10.1007/s11600-023-01154-w
942. Historical and future extremes of cauvery basin analysed using cmip6 models and ETCCDI indices S. Sridhara et al. https://doi.org/10.1038/s41598-026-42818-z
943. TISE-LSTM: A LSTM model for precipitation nowcasting with temporal interactions and spatial extract blocks C. Zheng et al. https://doi.org/10.1016/j.neucom.2024.127700
944. Estimating the Health Effects of Adding Bicycle and Pedestrian Paths at the Census Tract Level: Multiple Model Comparison R. Gore et al. https://doi.org/10.2196/37379
945. Correlating the Plant Height of Wheat with Above-Ground Biomass and Crop Yield Using Drone Imagery and Crop Surface Model, A Case Study from Nepal U. Panday et al. https://doi.org/10.3390/drones4030028
946. A comparative analysis of job satisfaction prediction models using machine learning: a mixed-method approach J. Kim et al. https://doi.org/10.1108/DTA-10-2023-0697
947. Non-Linear Impact of Organizational Structure on Schedule Management for R&D Project Success: An ANN Approach H. Hanif & A. Ahsan https://doi.org/10.22581/muet1982.1902.04
948. Advanced evasion attacks and mitigations on practical ML‐based phishing website classifiers F. Song et al. https://doi.org/10.1002/int.22510
949. Sensitive method for detecting tooth faults in gearboxes based on wavelet denoising and empirical mode decomposition S. Jin et al. https://doi.org/10.1007/s12206-015-0715-8
950. Optimizing CO2 Concentrations and Emissions Based on the WRF-Chem Model Integrated with the 3DVAR and EAKF Methods W. Liu et al. https://doi.org/10.3390/rs18010174
951. A Review of Deep Learning Models for Time Series Prediction Z. Han et al. https://doi.org/10.1109/JSEN.2019.2923982
952. Magnetic object positioning method based on tensor spacial invariant relations Q. Li et al. https://doi.org/10.1088/1361-6501/ab8dfe
953. Developing a vertical mixing device to enhance radio frequency heating uniformity of black peppercorns via discrete element method S. Bai et al. https://doi.org/10.1016/j.ifset.2026.104739
954. Characterization of spatio-temporal groundwater drought in Kalpathypuzha watershed, India R. Assainar K K et al. https://doi.org/10.1007/s40899-025-01254-z
955. Using machine learning as a surrogate model for agent-based simulations C. Angione et al. https://doi.org/10.1371/journal.pone.0263150
956. Adaptive RISE Feedback Control for Robotized Machining With PKMs: Design and Real-Time Experiments J. Escorcia-Hernandez et al. https://doi.org/10.1109/TCST.2022.3169015
957. ARM-SSM: Atrous Radio Map State Space Models for High-Resolution Wireless Environment Reconstruction Q. Zhang et al. https://doi.org/10.1109/TNSE.2026.3735078
958. Estimation of Leaf Water Content in Spring Wheat Based on UAV Multispectral Imagery J. Zhu et al. https://doi.org/10.3390/agronomy16090845
959. Semantic-Relation Transformer for Visible and Infrared Fused Image Quality Assessment Z. Chang et al. https://doi.org/10.1016/j.inffus.2023.02.021
960. Forecasting summer marine heatwaves in the South China Sea using explainable machine learning models C. Mi et al. https://doi.org/10.1016/j.dsr.2025.104457
961. Winter wheat plant density determination: Robust predictions across varied agronomic conditions using multiscale RGB imaging J. Jauregui-Besó et al. https://doi.org/10.1016/j.atech.2025.100921
962. Data-Driven harmonic forecasting in wave energy conversion systems using machine and deep learning A. Karadeniz https://doi.org/10.1016/j.epsr.2026.113920
963. Intrinsic heterogeneity in detection probability and its effect on N‐mixture models J. Veech et al. https://doi.org/10.1111/2041-210X.12566
964. Developing Cluster-Based Adaptive Network Fuzzy Inference System Tuned by Particle Swarm Optimization to Forecast Annual Automotive Sales: A Case Study in Iran Market S. Hasheminejad et al. https://doi.org/10.1007/s40815-022-01263-6
965. Development of a spatially contextualised and AI-enabled digital twin for asthma-specific indoor air quality management N. Khosh-Amadi et al. https://doi.org/10.1016/j.jobe.2025.115027
966. Seasonal performance in basal area estimation: a comparative study of a smartphone LiDAR application and a professional personal laser scanning J. Morocho Toaza & S. Borz https://doi.org/10.3389/ffgc.2026.1844787
967. Deep Learning-Based Sensor Array: 3D Fluorescence Spectra of Gold Nanoclusters for Qualitative and Quantitative Analysis of Vitamin B6 Derivatives H. Noreldeen et al. https://doi.org/10.1021/acs.analchem.2c00655
968. Time-series prediction of adverse birth outcomes in the U.S. using multilayer perceptron neural networks B. Hailu & P. Shi https://doi.org/10.1371/journal.pdig.0001515
969. Prediction of production rate of surface miner in coal mine: an application of single and ensemble machine learning methods A. Lawal et al. https://doi.org/10.1007/s12145-024-01342-2
970. A Respiratory Motion Prediction Method Based on Improved Relevance Vector Machine Q. Fan et al. https://doi.org/10.1007/s11036-020-01610-7
971. Predicting the bandgap and efficiency of perovskite solar cells using machine learning methods A. Khan et al. https://doi.org/10.1002/minf.202300217
972. Applying Data-Driven Modeling for Streamflow Prediction in Semi-Arid Watersheds: A Comparative Evaluation of Machine Learning and Deep Learning Methodologies M. Sarıgöl et al. https://doi.org/10.1007/s00024-024-03607-9
973. Expanding the range of ship fuel consumption prediction: A multi-algorithm feature selection approach S. Piao et al. https://doi.org/10.1016/j.oceaneng.2024.119944
974. Extending a scalable satellite-based vegetation edge detection framework to diverse tropical coasts I. Nugraha et al. https://doi.org/10.3389/fmars.2026.1757991
975. Employing long short-term memory and Facebook prophet model in air temperature forecasting T. Toharudin et al. https://doi.org/10.1080/03610918.2020.1854302
976. Generative adversarial networks in dental imaging: a systematic review S. Yang et al. https://doi.org/10.1007/s11282-023-00719-1
977. Development and Design of an Optimal Fuzzy Logic Two Degrees of Freedom-Proportional Integral Derivative Controller for a Two-Area Power System Using the Bee Algorithm S. Audomsi et al. https://doi.org/10.3390/en18040915
978. Variogram-distance graph attention Kriging: an innovative hybrid approach for improving soil heavy metals interpolation L. Zeng et al. https://doi.org/10.1007/s00477-026-03214-1
979. Development of a Deep-Learning Model for Estimating Newborn Gestational Age via Lumbar Vertebral Segmentation on Plain Radiography S. Ham et al. https://doi.org/10.3348/kjr.2025.0172
980. Spatial variability of soil organic matter and total nitrogen and the influencing factors in Huzhu County of Qinghai Province, China B. Zhang et al. https://doi.org/10.1080/09064710.2021.2023624
981. Improving land surface model accuracy in soil moisture simulations using parametric schemes and machine learning X. Zhao et al. https://doi.org/10.1016/j.jhydrol.2025.133109
982. Cut-SOAP: A Machine Learning Descriptor for Rapid Screening of Molecular Adsorption Energetics F. Calderan et al. https://doi.org/10.1021/acsomega.5c10055
983. Spatial transferability of machine and deep learning models for reference evapotranspiration estimation: Implications for climate-smart irrigation water management in Bangladesh M. Islam et al. https://doi.org/10.1016/j.htopen.2026.100061
984. NRA-Net—Neg-Region Attention Network for Salient Object Detection with Gaze Tracking H. Kim et al. https://doi.org/10.3390/s21051753
985. Location-Centered House Price Prediction: A Multi-Task Learning Approach G. Gao et al. https://doi.org/10.1145/3501806
986. Development of a fed-batch-scale anaerobic co-digestion control system based on multivariable output error state space and model predictive control R. Bai et al. https://doi.org/10.1016/j.rineng.2024.102284
987. Reservoir water budget estimation using satellite and ground measurement data S. Wahyuni et al. https://doi.org/10.1088/1755-1315/1311/1/012058
988. Population estimation beyond counts—Inferring demographic characteristics N. Szarka et al. https://doi.org/10.1371/journal.pone.0266484
989. A Survey of Artificial Intelligence Applications in Wind Energy Forecasting P. Dhaka et al. https://doi.org/10.1007/s11831-024-10182-8
990. Fusion of MODIS and Landsat-Like Images for Daily High Spatial Resolution NDVI R. Filgueiras et al. https://doi.org/10.3390/rs12081297
991. Standing wave-moving and sample-rotating effect of microwave heating on ceramic in a single-model cavity C. Haoming et al. https://doi.org/10.1080/08327823.2024.2341342
992. Mapping the Problem Areas in Diabetes (PAID) and Diabetes Distress Scale (DDS) to the EQ-5D-5L in diabetes care P. Arija et al. https://doi.org/10.1007/s11136-026-04361-2
993. Comparison of missing value estimation techniques in rainfall data of Bangladesh F. Jahan et al. https://doi.org/10.1007/s00704-018-2537-y
994. Enhancing Chemical Prediction in Plasma Protein Binding: A Deep Learning Model Combining Molecular Descriptors and Fingerprint Representation With Attention Mechanisms Q. Tian et al. https://doi.org/10.1109/TCBBIO.2025.3532332
995. Machine-Learning-Based Electric Power Forecasting G. Chen et al. https://doi.org/10.3390/su151411299
996. Numerical investigations on seasonal variation of waves in the Cat Ba – Ha Long coastal area (Vietnam) in 2021 M. Nguyen et al. https://doi.org/10.1016/j.rsma.2024.103828
997. A novel hybrid machine learning approach for δ13C spatial prediction in polish hard-water lakes H. Shahabi et al. https://doi.org/10.1016/j.ecoinf.2025.103187
998. New objective functions for streamflow calibrations to specific model applications H. Il Choi https://doi.org/10.1016/j.jhydrol.2024.132109
999. Comparative Study of Four Hybrid Spatiotemporal Models for Daily PM2.5 Prediction in the Chengdu–Chongqing Region B. Hu et al. https://doi.org/10.3390/su18063126
1000. In-situ recommendation of alternative soil samples during field sampling based on environmental similarity T. Ma et al. https://doi.org/10.1007/s12145-019-00407-x
1001. Leveraging Advanced Optimization Techniques with Deep Learning for Efficient Aerospace and Industrial Design J. Zerouaoui et al. https://doi.org/10.1051/e3sconf/202568000025
1002. Comparing Regression Models with Count Data to Artificial Neural Network and Ensemble Models for Prediction of Generic Escherichia coli Population in Agricultural Ponds Based on Weather Station Measurements G. Buyrukoğlu et al. https://doi.org/10.1016/j.mran.2021.100171
1003. Hydraulic river model calibration and validation for comprehensive hydrograph simulation: Evaluating accuracy across discharge ranges P. Kuhanestani et al. https://doi.org/10.1016/j.jhydrol.2025.133210
1004. Selección y aplicación de funciones Cópula con dependencia en su extremo derecho al análisis de frecuencias conjunto (Q, V) de crecientes anuales D. Campos-Aranda https://doi.org/10.24850/j-tyca-14-05-03
1005. Computational AI prediction models for residual tensile strength of GFRP bars aged in the alkaline concrete environment M. Iqbal et al. https://doi.org/10.1016/j.oceaneng.2021.109134
1006. IntelliChain: An Intelligent and Adaptive Framework for Decentralized Applications on Public Blockchain Technologies: An NFT Marketplace Case Study M. Rasolroveicy & M. Fokaefs https://doi.org/10.1109/TR.2024.3451964
1007. A dynamic predictive model for Bacillus cereus growth from spores under temperature abuse conditions V. Juneja et al. https://doi.org/10.1016/j.foodres.2026.119773
1008. Optimizing cereal yields in Morocco’s Favorable agro-ecological zone: Integrating dynamic vegetation modeling, machine learning, and climate projections for adaptive agricultural strategies I. Loudiyi et al. https://doi.org/10.1016/j.nxsust.2026.100298
1009. Electric Vehicle Charging Load Forecasting Based on K-Means++-GRU-KSVR R. Shang & Y. Ma https://doi.org/10.3390/wevj15120582
1010. An Object-Oriented Semi-Supervised Land-Use/Land-Cover Change Detection Method Based on Siamese Autoencoder Graph Attention Network Y. Wu et al. https://doi.org/10.1109/JSTARS.2024.3373039
1011. Developing an Uncrewed Aerial Vehicle (UAV)-Based Prediction Model for the Rice Harvest Index Using Machine Learning Z. Pan et al. https://doi.org/10.3390/agriculture15090971
1012. Distribution of strontium isotopes in river waters across the Tarim Basin: a map for migration studies X. Wang et al. https://doi.org/10.1144/jgs2018-074
1013. Estimating Historical Downside Risks of Global Financial Market Indices via Inflation Rate-Adjusted Dependence Graphs I. Choi & W. Kim https://doi.org/10.1016/j.ribaf.2023.102077
1014. Experimental investigation and modeling of CO 2 corrosion in enhanced oil recovery surface gathering pipelines X. Fu et al. https://doi.org/10.1080/10916466.2026.2712276
1015. Spatio-temporal variation of reference evapotranspiration in northwest China based on CORDEX-EA L. Yang et al. https://doi.org/10.1016/j.atmosres.2020.104868
1016. ROA and ROE Forecasting in Iron and Steel Industry Using Machine Learning Techniques for Sustainable Profitability M. Kayakus et al. https://doi.org/10.3390/su15097389
1017. Fuzzy risk stratification and risk assessment model for clinical monitoring in the ICU A. Dervishi https://doi.org/10.1016/j.compbiomed.2017.05.034
1018. Application of artificial neural networks in the prediction of sugarcane juice Pol A. Coelho et al. https://doi.org/10.1590/1807-1929/agriambi.v23n1p9-15
1019. Experimental estimation of the emissivity of human enamel and dentin A. Soori et al. https://doi.org/10.1016/j.infrared.2020.103234
1020. Prediction of soil heavy metal contents in urban residential areas and the strength of deep learning: A case study of Beijing Y. Hou et al. https://doi.org/10.1016/j.scitotenv.2024.175133
1021. Super-Resolution Reconstruction of Seafloor Topography Using ViT-GAN Model and 3-Arcsecond Multibeam Bathymetric Data Z. Zhang et al. https://doi.org/10.1109/JSTARS.2026.3716897
1022. Neural-based spatial-spectral sensitivity correction for push-brum hyperspectral cameras A. Makarov & A. Nikonorov https://doi.org/10.18287/COJ1812
1023. Why Do You Watch This Rough Stuff? Assessing Predictors of Female Pornography Preferences M. von Andrian-Werburg et al. https://doi.org/10.1080/00224499.2026.2642323
1024. Quantitative photoacoustic tomography with light fluence compensation based on radiance Monte Carlo model S. Zheng et al. https://doi.org/10.1088/1361-6560/acbe90
1025. Soil and Rockfill Dams Safety Assessment for Henan Province: Monitoring, Analysis and Prediction H. Liu et al. https://doi.org/10.3390/rs15174293
1026. Multi-agent collaboration strategies for tourism demand forecasting D. Wu et al. https://doi.org/10.1016/j.tourman.2026.105479
1027. R2 should not be used to describe behavioral‐economic discounting and demand models B. Gelino et al. https://doi.org/10.1002/jeab.4200
1028. Digital Mapping of Soil Physicochemical Properties for Sustainable Irrigation Management in a Semi-Arid Region of Central Mexico O. Galván-Cano et al. https://doi.org/10.3390/land15030398
1029. Combining Vegetation Indices to Identify the Maize Phenological Information Based on the Shape Model H. Wu et al. https://doi.org/10.3390/agriculture14091608
1030. Path Loss Considering Atmospheric Impact in 5G Networks: A Comparison of Machine Learning Models V. Rekkas et al. https://doi.org/10.3390/technologies14030151
1031. Control of denitration system in cement calcination process: A Novel method of Deep Neural Network Model Predictive Control Q. Xu et al. https://doi.org/10.1016/j.jclepro.2021.129970
1032. Prediction of nitrogen oxide emission concentration in cement production process: a method of deep belief network with clustering and time series X. Hao et al. https://doi.org/10.1007/s11356-021-12834-9
1033. Development of a Prediction Model for Specific Fuel Consumption in Rotary Tillage Based on Actual Operation S. Kim et al. https://doi.org/10.3390/agriculture14111993
1034. Enhancing User Emotion via a Session-Based News Recommender System Using Touch Interaction Patterns M. Parishani et al. https://doi.org/10.1080/10447318.2026.2702745
1035. Development of growth and survival models for Salmonella and Listeria monocytogenes during non-isothermal time-temperature profiles in leafy greens A. Mishra et al. https://doi.org/10.1016/j.foodcont.2016.06.009
1036. Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm R. Prasad et al. https://doi.org/10.1016/j.atmosres.2017.06.014
1037. Toward the Fractal Dimension of Classes W. Pan et al. https://doi.org/10.1145/3688844
1038. Using Wikipedia to Predict Election Outcomes B. Smith & A. Gustafson https://doi.org/10.1093/poq/nfx007
1039. Improving impervious surface estimation: an integrated method of classification and regression trees (CART) and linear spectral mixture analysis (LSMA) based on error analysis J. Wang et al. https://doi.org/10.1080/15481603.2017.1417690
1040. Antarctic Verification of the Australian Numerical Weather Prediction Model B. Schroeter et al. https://doi.org/10.1175/WAF-D-18-0171.1
1041. On the accuracy and computational cost of spiking neuron implementation S. Valadez-Godínez et al. https://doi.org/10.1016/j.neunet.2019.09.026
1042. Evaluation of Machine Learning Application on the Prediction of Particulate Matter Concentrations in Small/Medium-Sized City Y. Lee et al. https://doi.org/10.4491/KSEE.2024.46.10.537
1043. Design of ANFIS for Hydrophobicity Classification of Polymeric Insulators with Two-Stage Feature Reduction Technique and Its Field Deployment R. Jayabal et al. https://doi.org/10.3390/en11123391
1044. An explainable machine learning model for encompassing the mechanical strength of polymer-modified concrete M. Sobuz et al. https://doi.org/10.1007/s42107-024-01230-6
1045. Estimation of Effective Length of Type-A Grounding System According to IEC 62305-3 Using a Machine Learning Regression Model D. Lovrić et al. https://doi.org/10.3390/app14166945
1046. Assembly torque data regression using sEMG and inertial signals C. Chen et al. https://doi.org/10.1016/j.jmsy.2021.04.011
1047. Performance evaluation of varies climate models using observed and regional climate models for the Katar Watershed, Ethiopia B. Yersaw et al. https://doi.org/10.1186/s40068-024-00345-8
1048. Development of an Artificial Intelligence Approach for Prediction of Consolidation Coefficient of Soft Soil: A Sensitivity Analysis M. Nguyen et al. https://doi.org/10.2174/1874836801913010178
1049. Reducing penumbral blur in computed tomography by learning the inverse finite focal spot model H. Yu et al. https://doi.org/10.1364/OE.527304
1050. Single-Channel Blind Signal Separation of the MHD Linear Vibration Sensor Based on Singular Spectrum Analysis and Fast Independent Component Analysis M. Xu et al. https://doi.org/10.3390/s22249657
1051. An investigation of multivariate data-driven deep learning models for predicting COVID-19 variants A. Baihaqi et al. https://doi.org/10.1016/j.health.2024.100331
1052. An Innovative Machine Learning Model to Formulate the Bearing Capacity of Concrete-Filled Steel Tube Column A. Abbasi et al. https://doi.org/10.1007/s13369-024-09148-6
1053. Uncertainty of the 2D Resistivity Survey on the Subsurface Cavities Y. Doyoro et al. https://doi.org/10.3390/app11073143
1054. Adaptive Analysis of Green Space Network Planning for the Cooling Effect of Residential Blocks in Summer: A Case Study in Shanghai Y. Jiang et al. https://doi.org/10.3390/su10093189
1055. An optimized strategy for density prediction of intermetallics across varied crystal structures via graph neural network D. Zhu et al. https://doi.org/10.20517/jmi.2024.76
1056. A new supervised learning framework for mineral prospectivity mapping: The three-class labeling (3CL) approach S. Qaderi & A. Maghsoudi https://doi.org/10.1016/j.gexplo.2025.107831
1057. Mammalian faunas, ecological indices, and machine-learning regression for the purpose of paleoenvironment reconstruction in the Miocene of South America J. Spradley et al. https://doi.org/10.1016/j.palaeo.2019.01.014
1058. Building a ML-based QSAR model for predicting the bioactivity of therapeutically active drug class with imidazole scaffold K. Singh et al. https://doi.org/10.1016/j.ejmcr.2024.100148
1059. Ensemble Modeling for Global Forecasting of Monkeypox Incidence Using Statistical and Machine Learning Approaches M. Parvin et al. https://doi.org/10.1155/acis/6094718
1060. Dissolved oxygen concentration predictions for running waters with using hybrid machine learning techniques R. Dehghani et al. https://doi.org/10.1007/s40808-021-01253-x
1061. Metaverse token price forecasting using artificial neural networks (ANNs) and Adaptive neural fuzzy inference system (ANFIS) İ. Özkal et al. https://doi.org/10.1007/s00521-023-09228-y
1062. Diesel Engine Power Prediction Based on Fuel Blends Using Neural Network R. Naryanto et al. https://doi.org/10.31181/rme492
1063. Estimation of Forest Aboveground Biomass of Two Major Conifers in Ibaraki Prefecture, Japan, from PALSAR-2 and Sentinel-2 Data H. Li et al. https://doi.org/10.3390/rs14030468
1064. Tower Crane–Mounted Multisensor System for Real-Time 3D Spatial Mapping in Modular Integrated Construction A. Ali et al. https://doi.org/10.1061/JCEMD4.COENG-18680
1065. Comparative evaluation of supervised machine learning algorithms in the prediction of the relative density of 316L stainless steel fabricated by selective laser melting G. Barrionuevo et al. https://doi.org/10.1007/s00170-021-06596-4
1066. Simulating the impacts of fishing on central and eastern tropical Pacific ecosystem using multispecies size-spectrum model Q. Lin et al. https://doi.org/10.1007/s13131-021-1902-3
1067. Hierarchical optimization of perovskite solar cell fabrication via step-by-step machine learning Y. Pu et al. https://doi.org/10.1016/j.xcrp.2025.103043
1068. Evaluating Model Predictions of Fire Induced Tree Mortality Using Wildfire-Affected Forest Inventory Measurements J. Barker et al. https://doi.org/10.3390/f10110958
1069. In silico soil degradation and ecotoxicity analysis of veterinary pharmaceuticals on terrestrial species: first report P. Banjare et al. https://doi.org/10.1093/toxres/tfae020
1070. Blast Response and Multi-Objective Optimization of Stretching–Bending Synergistic Lattice Core Sandwich Panels X. Gao & L. Long https://doi.org/10.3390/app16062799
1071. Time series model for forecasting the number of new admission inpatients L. Zhou et al. https://doi.org/10.1186/s12911-018-0616-8
1072. Assessment of runoff in Chandra river basin of Western Himalaya using Remote Sensing and GIS Techniques V. Gaddam et al. https://doi.org/10.1007/s10661-022-09795-y
1073. Study of forward–backward solute dispersion profiles in a semi-infinite groundwater system M. Singh et al. https://doi.org/10.1080/02626667.2020.1740706
1074. Inter-comparison of remotely sensed precipitation datasets over Kenya during 1998–2016 B. Ayugi et al. https://doi.org/10.1016/j.atmosres.2019.03.032
1075. Influence of machining parameters on dynamic errors in a hexapod machining cell K. Xing et al. https://doi.org/10.1007/s00170-024-12968-3
1076. An Ecological Expert System Optimization for Assessing Environmental Water Requirements of Hypersaline Lakes M. Sedighkia & A. Abdoli https://doi.org/10.1007/s13157-022-01614-x
1077. Effect of Poisson's ratio on the indentation of open cell foam O. Duncan et al. https://doi.org/10.1016/j.euromechsol.2023.104922
1078. Canada’s human footprint reveals large intact areas juxtaposed against areas under immense anthropogenic pressure K. Hirsh-Pearson et al. https://doi.org/10.1139/facets-2021-0063
1079. New species-specific allometric models for above- and below-ground biomass and carbon content of young mangroves B. Okarda et al. https://doi.org/10.1016/j.gecco.2026.e04155
1080. Modeling Energy LED Light Consumption Based on an Artificial Intelligent Method Applied to Closed Plant Production System E. Olvera-Gonzalez et al. https://doi.org/10.3390/app11062735
1081. Extraction of Measurement Device Information on an ESP32 Microcontroller: TinyML for Image Processing J. Paul et al. https://doi.org/10.1016/j.procs.2024.09.670
1082. Seasonal pattern of dengue infection in Singapore: A mechanism-based modeling and prediction I. Fauzi et al. https://doi.org/10.1016/j.ecolmodel.2024.111003
1083. Hybrid simulation and labor allocation for optimized commercial construction scheduling during COVID-19 A. AlTarabsheh https://doi.org/10.1108/ECAM-04-2025-0710
1084. Benchmarking parametric models of disease progression for early detection of cognitive decline C. Platero & J. Bengoa https://doi.org/10.1016/j.cmpb.2025.109162
1085. Machine Learning-Driven Prediction of Thermal Conductivity in Reaction-Bonded Silicon Nitride Ceramics C. Mittal et al. https://doi.org/10.1007/s12633-026-03771-8
1086. Benthic ecosystem functioning under climate change: modelling the bioturbation potential for benthic key species in the southern North Sea M. Weinert et al. https://doi.org/10.7717/peerj.14105
1087. Türkiye’nin 2030 CO2 Emisyon Hedefinin Holt-Winters Üstel Düzeltme Modeli ile Tahmini İ. Dinçel Kıratoğlu https://doi.org/10.33203/mfy.1834216
1088. What can we learn from multi-data calibration of a process-based ecohydrological model? S. Kuppel et al. https://doi.org/10.1016/j.envsoft.2018.01.001
1089. Predicting IRI Using Machine Learning Techniques A. Sharma et al. https://doi.org/10.1007/s42947-021-00119-w
1090. Study on the Improvement of the Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise in Hydrology Based on RBFNN Data Extension Technology J. Zhang et al. https://doi.org/10.32604/cmes.2021.012686
1091. QSPR models for predicting the Kovats retention indices of synthetic ester derivatives based on pyrethrin essential oil M. Sadeghi et al. https://doi.org/10.1080/10412905.2023.2265376
1092. Assessment of bias correction technique to improve ozone reanalysis dataset over India T. Gangwar et al. https://doi.org/10.1007/s42865-025-00109-x
1093. Real-Time Implementation of State-Feedback Learning Framework for Bipedal Locomotion Over Undulating Surfaces B. Singh et al. https://doi.org/10.1109/TMECH.2024.3380190
1094. Evaluation of Railway Passenger Comfort With Machine Learning J. Huang & S. Kaewunruen https://doi.org/10.1109/ACCESS.2021.3139465
1095. Comfort-based design of summer green space optimization in arid oasis-type cities H. Xie et al. https://doi.org/10.1016/j.jtherbio.2024.104020
1096. Interpretable streamflow prediction in headwater area of the Yellow River using a climate-adaptive transformer and SHAP under CMIP6 scenarios J. Xu et al. https://doi.org/10.1016/j.jenvman.2026.129694
1097. On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study D. de Souza et al. https://doi.org/10.3390/su132413599
1098. Predicting optimal membrane hydration and ohmic losses in operating fuel cells with machine learning J. Paciocco et al. https://doi.org/10.1016/j.jpowsour.2023.233119
1099. A Supervised Learning Process to Validate Online Disease Reports for Use in Predictive Models H. Patching et al. https://doi.org/10.1089/big.2015.0019
1100. Time Aggregation in Presence of Multiple Variable Energy Resources N. Sarajpoor et al. https://doi.org/10.1109/TPWRS.2023.3236842
1101. The impacts of commercial plantation forests on groundwater recharge: A case study from George (Western Cape, South Africa) N. Tuswa et al. https://doi.org/10.1016/j.pce.2018.12.006
1102. Updated Lagrangian Particle Hydrodynamics (ULPH) modeling and simulation of multiphase flows J. Yan et al. https://doi.org/10.1016/j.jcp.2019.05.017
1103. A Sustainable Price Prediction Model for Airbnb Listings Using Machine Learning and Sentiment Analysis Z. Alharbi https://doi.org/10.3390/su151713159
1104. Appraising city-scale pollution monitoring capabilities of multi-satellite datasets using portable pollutant monitors Y. Aliyu & J. Botai https://doi.org/10.1016/j.atmosenv.2018.02.034
1105. Evaluating the Performance of Land Surface Models and Microphysics Schemes on Simulation of an Extreme Rainfall Event in Tanzania Using the Weather Research and Forecasting Model D. Mwageni et al. https://doi.org/10.4236/acs.2025.151003
1106. Comparison of Parametric and Nonparametric Methods for Analyzing the Bias of a Numerical Model I. Mugume et al. https://doi.org/10.1155/2016/7530759
1107. Intelligent algorithm-driven optimization for turnout rail grinding strategy and carbody vibration suppression Y. Yang et al. https://doi.org/10.1080/00423114.2025.2570879
1108. Time-series projecting road traffic fatalities in Australia: Insights for targeted safety interventions A. Soltani et al. https://doi.org/10.1016/j.injury.2025.112166
1109. Energy Forecasting in Buildings Using Deep Neural Networks M. Migliori & H. Najafi https://doi.org/10.1115/1.4063213
1110. Prediction model of microclimatic surface conditions on building façades S. Charisi et al. https://doi.org/10.1016/j.buildenv.2017.11.017
1111. Prediction of malaria using deep learning models: A case study on city clusters in the state of Amazonas, Brazil, from 2003 to 2018 M. Barboza et al. https://doi.org/10.1590/0037-8682-0420-2021
1112. High-throughput unmanned aerial vehicle-based phenotyping provides insights into the dynamic process and genetic basis of rapeseed waterlogging response in the field J. Li et al. https://doi.org/10.1093/jxb/erac242
1113. Evaluation of the BMA probabilistic inflow forecasts using TIGGE numeric precipitation predictions based on artificial neural network Y. Zhong et al. https://doi.org/10.2166/nh.2018.177
1114. Comparative Analysis and Validation of LSTM and GRU Models for Predicting Annual Mean Sea Level in the East Sea: A Case Study of Ulleungdo Island T. Kim et al. https://doi.org/10.3390/app152011067
1115. ANFIS-Driven Optimization of Indoor Navigation Systems for Automated Guided Vehicles Utilizing UWB Signals A. Yüksek & A. Elik https://doi.org/10.66248/cumfad.1680103
1116. Evaluating the use of machine learning in the assessment of joint angle using a single inertial sensor R. Argent et al. https://doi.org/10.1177/2055668319868544
1117. Machine learning-based performance optimization of graphite matrix composite with paraffin for thermal energy storage applications M. Yazici et al. https://doi.org/10.1016/j.applthermaleng.2026.132033
1118. BiCross-STFNet: Significant Wave Height Inversion Based on Spatiotemporal-Frequency Feature Fusion L. Wu et al. https://doi.org/10.1109/TGRS.2025.3625290
1119. Hybrid Deep Learning Models for Predicting Saltwater Intrusion in Nearshore Aquifers: Comparative Evaluation of CNN, LSTM, and DNN Architectures D. Roy et al. https://doi.org/10.3390/w18131544
1120. Development of a hybrid stacked machine learning model for predicting compressive strength of high-performance concrete R. Tipu et al. https://doi.org/10.1007/s42107-023-00689-z
1121. Robust classification of heart valve sound based on adaptive EMD and feature fusion W. Wang et al. https://doi.org/10.1371/journal.pone.0276264
1122. Assessment of Deep Neural Network Models for Direct and Recursive Multi-Step Prediction of PM10 in Southern Spain J. Gómez-Gómez et al. https://doi.org/10.3390/forecast7010006
1123. Green Inhibitor Performance against CaCO3 Scaling: Rate-Modeling Aided Test Procedure M. Wedenig et al. https://doi.org/10.1021/acs.cgd.0c01258
1124. Singular value decomposition‐based load indexes for load profiles clustering Z. Wang et al. https://doi.org/10.1049/iet-gtd.2019.1960
1125. Revisiting Forest Effects on Winter Air Temperature and Wind Speed—New Open Data and Transfer Functions M. Klein et al. https://doi.org/10.3390/atmos12060710
1126. Modeling of necking area reduction of carbon steel in hydrogen environment using machine learning approach N. Ahmed et al. https://doi.org/10.1016/j.engfailanal.2023.107864
1127. Study of mesh sensitivity and temporal discretization influence on the generation of realistic irregular waves through the WaveMIMO methodology M. Paiva et al. https://doi.org/10.5902/2179460X87167
1128. Sensitivity and optimization CFD analysis of a vane-type pipe separator based on the AIAD model H. Zhang & T. Höhne https://doi.org/10.1016/j.ijmultiphaseflow.2025.105510
1129. Validation of a deep learning segmentation algorithm to quantify the skeletal muscle index and sarcopenia in metastatic renal carcinoma V. Roblot et al. https://doi.org/10.1007/s00330-022-08579-9
1130. Enhancing Model Generalizability in Aircraft Carbon Brake Wear Prediction: A Comparative Study and Transfer Learning Approach P. Jammal et al. https://doi.org/10.3390/aerospace12060555
1131. A Machine Learning Approach to Solve the Network Overload Problem Caused by IoT Devices Spatially Tracked Indoors D. Carvalho et al. https://doi.org/10.3390/jsan11020029
1132. Fusing meteorological factors and baidu search index with an adapted deformtime model to predict influenza-like illness in Beijing L. Shen et al. https://doi.org/10.3389/fpubh.2026.1856514
1133. A comparative study of artificial neural networks in predicting blast-induced air-blast overpressure at Deo Nai open-pit coal mine, Vietnam H. Nguyen et al. https://doi.org/10.1007/s00521-018-3717-5
1134. Predictive models for dynamic properties of soils using machine learning approaches: A comprehensive review S. Ghorbanzadeh et al. https://doi.org/10.1016/j.engappai.2025.113014
1135. Optimizing spatial positioning of traps in the context of integrated pest management R. Guimapi et al. https://doi.org/10.1016/j.ecocom.2019.100808
1136. Statistical and machine learning hybridization for predicting shear wave velocity in tight sand reservoirs: A case study A. Ismail et al. https://doi.org/10.1016/j.geoen.2023.212420
1137. Inverted Algorithm of Terrestrial Water-Storage Anomalies Based on Machine Learning Combined with Load Model and Its Application in Southwest China Y. Shen et al. https://doi.org/10.3390/rs13173358
1138. Computerized Bone Age Estimation Using Deep Learning Based Program: Evaluation of the Accuracy and Efficiency J. Kim et al. https://doi.org/10.2214/AJR.17.18224
1139. Precipitation recycling impacts on runoff in arid regions of China and Mongolia: a machine learning approach R. Li et al. https://doi.org/10.1080/02626667.2025.2456211
1140. Lightweight membrane-type acoustic meta-panel with flexible/hierarchical cells for the low-frequency sound insulation A. Soleimani Khoshru & D. Younesian https://doi.org/10.1177/1351010X251412548
1141. Machine Learning-Based Estimation of Ground Reaction Forces and Knee Joint Kinetics from Inertial Sensors While Performing a Vertical Drop Jump S. Cerfoglio et al. https://doi.org/10.3390/s21227709
1142. TTDI: Transformer Based Truthful Data Inference in Sparse Mobile Crowdsensing X. Fu et al. https://doi.org/10.1109/TMC.2025.3635141
1143. AI-Based Indoor Localization Using Virtual Anchors in Combination with Wake-Up Receiver Nodes S. Chiboub et al. https://doi.org/10.3390/electronics15030584
1144. An autonomous resource provisioning framework for massively multiplayer online games in cloud environment M. Ghobaei-Arani et al. https://doi.org/10.1016/j.jnca.2019.06.002
1145. Prediction of Concrete Dam Deformation through the Combination of Machine Learning Models P. Alocén et al. https://doi.org/10.3390/w14071133
1146. Machine learning methods as a tool to analyse incomplete or irregularly sampled radon time series data M. Janik et al. https://doi.org/10.1016/j.scitotenv.2018.02.233
1147. Mathematical Assessment of the Role of Human Behavior Changes on SARS-CoV-2 Transmission Dynamics in the United States B. Pant et al. https://doi.org/10.1007/s11538-024-01324-x
1148. Validation of Climate Hazard Group InfraRed Precipitation with Station (CHIRPS) Data in Wonorejo Reservoir, Indonesia S. Wahyuni et al. https://doi.org/10.1088/1755-1315/930/1/012042
1149. On Real-Time Detection of Line Sags in Overhead Power Grids Using an IoT-Based Monitoring System: Theoretical Basis, System Implementation, and Long-Term Field Verification J. Jiang et al. https://doi.org/10.1109/JIOT.2021.3139933
1150. Sebaran Sedimen Dasar Perairan dan Pola Arus Laut Di Muara Sungai Loji, Pekalongan M. Pawitra et al. https://doi.org/10.14710/ijoce.v4i3.13443
1151. A practical time-domain nuclear magnetic resonance-based method for empirical assessment of homogeneity in amorphous solid dispersions A. Furuse et al. https://doi.org/10.1016/j.ijpharm.2026.127210
1152. Similarity measures in automated essay scoring systems: A ten-year review V. Ramnarain-Seetohul et al. https://doi.org/10.1007/s10639-021-10838-z
1153. Forecasting Hydrogen Vehicle Refuelling for Sustainable Transportation: A Light Gradient-Boosting Machine Model N. Isaac & A. Saha https://doi.org/10.3390/su16104055
1154. A Machine Learning-Based Model for Breast Volume Prediction Using Preoperative Anthropometric Measurements M. Akhoondinasab et al. https://doi.org/10.1007/s00266-022-02937-0
1155. Chain-based machine learning for full PVT data prediction K. Ghorayeb et al. https://doi.org/10.1016/j.petrol.2021.109658
1156. Performance Factors of Foreign Players Contributing to Team Success in Korean Women’s Volleyball J. Chung & D. Lee https://doi.org/10.2174/011875399X493227260902043350
1157. Spatially Explicit Explainable Machine Learning Reveals Heterogeneous Drivers of Fire Occurrence in the Southwestern Amazon L. Miguel & R. Moreira https://doi.org/10.1016/j.rsase.2026.102318
1158. Extreme-value Distribution Analysis of the Second CHIME/FRB Catalog: Assessing the Rarity of the One-off FRB 20250316A W. Zhang 张 & J. Wei 魏 https://doi.org/10.3847/1538-4357/ae5e74
1159. Spatiotemporal Interpolation Using Graph Neural Network S. Yao & B. Huang https://doi.org/10.1080/24694452.2023.2206469
1160. An Integrative Approach Towards Recommending Farming Solutions for Sustainable Agriculture V. Ghuriani et al. https://doi.org/10.18006/2023.11(2).306.315
1161. Research on determining the piles bearing capacity using a random forest model considering the randomness of the soil data V. Giap et al. https://doi.org/10.59382/j-ibst.2023.vi.vol2-5
1162. Next-Generation Drought Forecasting: Hybrid AI Models for Climate Resilience J. Liu et al. https://doi.org/10.3390/rs17203402
1163. A compositional approach to modeling cause-specific mortality with zero counts Z. Dong et al. https://doi.org/10.1017/S1748499524000320
1164. Development of artificial intelligence for modeling wastewater heavy metal removal: State of the art, application assessment and possible future research S. Bhagat et al. https://doi.org/10.1016/j.jclepro.2019.119473
1165. Analysis of social interactions in group-housed animals using dyadic linear models J. Han et al. https://doi.org/10.1016/j.applanim.2022.105747
1166. Cement-based grouting material development and prediction of material properties using PSO-RBF machine learning X. Liu et al. https://doi.org/10.1016/j.conbuildmat.2024.135328
1167. A new framework to assess multi-source precipitation products in China's river basins seasonality, events and extremes S. Li et al. https://doi.org/10.1016/j.atmosres.2026.109397
1168. Best practices for machine learning strategies aimed at process parameter development in powder bed fusion additive manufacturing N. Samadiani et al. https://doi.org/10.1007/s10845-024-02490-4
1169. Mapping and Analyzing Winter Wheat Yields in the Huang-Huai-Hai Plain: A Climate-Independent Perspective Y. Zhao et al. https://doi.org/10.3390/rs17081409
1170. Short-Term Electricity Price Forecasting: A Review of Point Forecasting Methods, Metrics, and Empirical Evaluation P. Piotrowski et al. https://doi.org/10.3390/en19174000
1171. Environmental and economic impacts and trade-offs from simultaneous management of soil constraints, nitrogen and water S. Kodur et al. https://doi.org/10.1016/j.jclepro.2019.03.079
1172. Hydrologic responses to climate and land-use/land-cover changes in the Bilate catchment, Southern Ethiopia H. Kuma et al. https://doi.org/10.2166/wcc.2021.281
1173. A method for recovering adversarial samples with both adversarial attack forensics and recognition accuracy Z. Chen et al. https://doi.org/10.1016/j.cose.2024.103987
1174. Machine learning-based prediction of design parameters for miniaturized textile antennas in the sub-6 GHz spectrum A. Devapriya & S. Robinson https://doi.org/10.1080/17455030.2025.2579926
1175. Enhancing large-scale chlorophyll-a estimation across U.S. Lakes through spectral and spatio-temporal feature integration: a machine learning approach using AquaMatch E. Agyekum & L. Li https://doi.org/10.1016/j.isprsjprs.2026.10.013
1176. Irradiated mechanical properties predicted by a machine learning method with the Fourier-transform-based feature extension Y. Dong et al. https://doi.org/10.1080/00223131.2023.2267044
1177. Kelulut stingless bee honey stored under different thermal conditions: Non-destructive assessment Y. Chin et al. https://doi.org/10.21603/2308-4057-2026-1-656
1178. Analysis and prediction of mechanical and thermal properties of unfired clay bricks with additives using random forest and support vector machine algorithms Y. Abdellaoui et al. https://doi.org/10.1016/j.jobe.2026.115763
1179. A machine learning-assisted multi-criteria decision making framework for chemical reactor channel geometry selection M. Kaya et al. https://doi.org/10.1016/j.cej.2026.178541
1180. Harnessing Machine Learning Models to Predict Flow Regimes over Stepped Spillways J. Weekaew et al. https://doi.org/10.48084/etasr.10159
1181. New ecological insights using size-specific species distribution models S. Smoliński et al. https://doi.org/10.1093/icesjms/fsag065
1182. Visibility Prediction and Diagnostic Interpretation Based on Comparative Modelling for Sustainable Urban Environmental Management: A Chengdu Study from November 2021 to October 2024 B. Hu et al. https://doi.org/10.3390/atmos17080765
1183. Spatiotemporal Approaches for Quality Control and Error Correction of Atmospheric Data through Machine Learning H. Kim et al. https://doi.org/10.1155/2020/7980434
1184. Comparison of the Moist Material Relative Permittivity Readouts Using the Non-Invasive Reflectometric Sensors and Microwave Antenna Z. Suchorab et al. https://doi.org/10.3390/s22103622
1185. The performance analysis of global ionospheric total electron content models over Türkiye region under low solar activity conditions O. Kayacik et al. https://doi.org/10.1007/s12648-025-03724-8
1186. A hybrid model based on chaos particle swarm optimization for significant wave height prediction C. Yang et al. https://doi.org/10.1016/j.ocemod.2025.102511
1187. Neural Arithmetic Logic Units with Two Transition Matrix and Independent Gates S. Passo et al. https://doi.org/10.1016/j.engappai.2024.109663
1188. Real-time detection and intelligent sorting algorithm for strawberry bruise in food applications Y. Wang et al. https://doi.org/10.1016/j.jfca.2025.108467
1189. Water Availability Trends in an Amazon River Basin Under Future Climate Scenarios A. de Cássia Lobato Soares et al. https://doi.org/10.1007/s10666-026-10161-2
1190. Improving UWB ranging accuracy via multiple network model with second order motion prediction G. Xing et al. https://doi.org/10.1007/s10586-023-04080-0
1191. Evaluating Seasonal Variability in Rainfall Forecast Accuracy Using Comparative Regression Modelling Approaches S. M. et al. https://doi.org/10.1007/s11269-026-04597-0
1192. Improving statistical obsolescence forecasting accuracy in the absence of covariate predictors through time-aware validation and binning strategy M. Sherwin et al. https://doi.org/10.1080/09544828.2026.2639937
1193. What Is an Oval, Officially and Overall? Old and New Mathematical Descriptions V. Narushin et al. https://doi.org/10.3390/computation14050101
1194. Satellite-Derived Precipitation Trends and ENSO-Related Anomalies in the Pindaré River Watershed, Northeastern Amazon Biome L. Goulart Fiscina et al. https://doi.org/10.1007/s41748-025-00743-7
1195. Design of optimal environmental flow regime at downstream of reservoirs using wetted perimeter-optimization method M. Sedighkia et al. https://doi.org/10.1016/j.jher.2021.09.001
1196. Maximum likelihood estimation for scale-shape mixtures of flexible generalized skew normal distributions via selection representation A. Mahdavi et al. https://doi.org/10.1007/s00180-021-01079-2
1197. Deep learning versus manual measurement of hallux valgus angle and intermetatarsal angle on Weight-Bearing X-rays in hallux valgus Q. Wang et al. https://doi.org/10.1186/s12891-025-09420-2
1198. Machine learning-based prediction of erosion wear and physical properties of Linz-Donawitz slag-reinforced epoxy composites for tribological applications P. Pati et al. https://doi.org/10.1016/j.nxmate.2026.103746
1199. LitePCT-BR: An interpretable multi-scale architecture for the recognition and prediction of train driver attentional decline D. Yu et al. https://doi.org/10.1016/j.aei.2026.104585
1200. Development of QSPR-ANN models for the estimation of critical properties of pure hydrocarbons M. Roubehie Fissa et al. https://doi.org/10.1016/j.jmgm.2023.108450
1201. Allometric Models to Estimate the Merchantable Wood Volume and Biomass of the Most Abundant Miombo Species in the Miombo Woodlands in Mozambique A. Manjate et al. https://doi.org/10.3390/earth6020052
1202. Design exploration and kinematic validation of a transtibial prosthesis using a 2SPU-RU parallel mechanism V. Abarca et al. https://doi.org/10.1007/s11370-025-00646-6
1203. Predicting compressive strength of lightweight foamed concrete using extreme learning machine model Z. Yaseen et al. https://doi.org/10.1016/j.advengsoft.2017.09.004
1204. Measurement of the Thin Liquid Film at the Wet-Gas Outlet of the Supersonic Separator by FPC Conductance Sensor H. Ding et al. https://doi.org/10.1109/TIM.2023.3273670
1205. Real-time prediction and inverse design of multiphase CO2 trapping in deep saline aquifers using machine learning enhanced by SHAP analysis S. Cheng et al. https://doi.org/10.1016/j.jgsce.2025.205782
1206. Comprehensive evaluation of parameter importance and optimization based on the integrated sensitivity analysis system: A case study of the BTOP model in the upper Min River Basin, China L. Liu et al. https://doi.org/10.1016/j.jhydrol.2022.127819
1207. A Framework for In Situ Rock UCS Assessment and Full‐Hole Strength Inversion Integrating MWD Signals and Symbolic Regression Strategies S. Huang et al. https://doi.org/10.1002/nag.70368
1208. Measurement-Driven Modeling of End-to-End Latency in an Indoor Private Standalone 5G Network O. Bodur et al. https://doi.org/10.3390/network6030078
1209. New Constitutive Matrix in the 3D Cell Method to Obtain a Lorentz Electric Field in a Magnetic Brake J. Monzón-Verona et al. https://doi.org/10.3390/s18103185
1210. Deep learning-based prediction of negative air ion concentrations using TCN-attention and meteo-temporal fusion transformer G. Zhang et al. https://doi.org/10.3389/fenvs.2026.1823488
1211. Embedding intelligent eco-aware systems within everyday things to increase people’s energy awareness D. Casado-Mansilla et al. https://doi.org/10.1007/s00500-015-1751-0
1212. Impact of Sampling Type, Frequency, and Scale of the Collection System on SARS-CoV-2 Quantification Fidelity A. George et al. https://doi.org/10.1021/acs.estlett.1c00882
1213. Computer vision to predict cell seeding coverage in re-endothelialized mouse lungs J. Paciocco et al. https://doi.org/10.1038/s41598-025-11272-8
1214. Evaluating the Performance and Clinical Utility of AI-driven Diagnostic Tools in Radiology S. Mercaldo et al. https://doi.org/10.1148/radiol.243935
1215. Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: A new approach R. Deo et al. https://doi.org/10.1016/j.rser.2019.01.009
1216. Estimation of the Torques Produced by Human Upper Limb during Eating Activities Using NARX-NN Z. Hussain & N. Zainul Azlan https://doi.org/10.1080/08839514.2022.2033472
1217. Intelligent digital twin – machine learning system for real-time wind turbine wind speed and power generation forecasting E. Tuton et al. https://doi.org/10.1051/e3sconf/202343301008
1218. Plasma gasification based monetization of poultry litter: System optimization and comprehensive 5E (Energy, Exergy, Emergy, Economic, and Environmental) analysis Y. Ayub et al. https://doi.org/10.1016/j.enconman.2023.116878
1219. Recent advances on deep residual learning based seismic data reconstruction: an overview N. Liu et al. https://doi.org/10.1093/jge/gxaf011
1220. Review of machine learning methods for sea level change modeling and prediction A. Ayinde et al. https://doi.org/10.1016/j.scitotenv.2024.176410
1221. VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM D. Tian et al. https://doi.org/10.1007/s11356-024-33293-y
1222. Alternate pathway for regional flood frequency analysis in data-sparse region N. Mangukiya & A. Sharma https://doi.org/10.1016/j.jhydrol.2024.130635
1223. Surrogate-based uncertainty quantification framework for Reynolds-averaged Navier-Stokes simulations of hypersonic large cone-flares C. El Khoury & J. Hickey https://doi.org/10.1016/j.ast.2026.113130
1224. Analysis of rainfall epochs in changing climate of Kangsabati river basin, India S. Chakraborty & T. Roshni https://doi.org/10.14712/23361980.2025.7
1225. Global and Regional Trends in Multiple Sclerosis Incidence with Projections to 2030: A Joinpoint Regression Analysis of the GBD Data 2021 by Socio‑Demographic Index and WHO Regions H. Delam et al. https://doi.org/10.5334/aogh.5438
1226. An Air Traffic Rebound Comparison Between Romania and the European Union: A Post-Pandemic Scenario of Boarding-Time Minimization Potential A. Stănescu et al. https://doi.org/10.3390/aerospace13090852
1227. Climate-adaptive transportation infrastructure: Cross-regional solutions for urban resilience and emergency response J. Tong et al. https://doi.org/10.1016/j.uclim.2026.102780
1228. Recovering Scene Geometry and Material from Event Streams with 3D Gaussian Splatting Z. Chen et al. https://doi.org/10.3390/s26175584
1229. Potential of Deep Learning in drought assessment by extracting information from hydrometeorological precursors R. Maity et al. https://doi.org/10.2166/wcc.2021.062
1230. High-resolution precipitation downscaling in mainland Southeast Asia: A novel integration of BMA and U-Net CNN T. Amnuaylojaroen https://doi.org/10.1016/j.envsoft.2025.106682
1231. An extrapolative machine learning framework for forecasting nitrogen oxide mitigation in alcohol enhanced ammonia-methane blends A. Shateri et al. https://doi.org/10.1016/j.egyai.2026.100705
1232. Prediction and Optimization of the Restoration Quality of University Outdoor Spaces: A Data-Driven Study Using Image Semantic Segmentation and Explainable Machine Learning X. Zhuang et al. https://doi.org/10.3390/buildings15162936
1233. ĐÁNH GIÁ TÁC ĐỘNG CỦA ĐIỀU KIỆN BÃO ĐẾN ĐẶC ĐIỂM VẬN CHUYỂN BÙN CÁT VÙNG CỬA SÔNG VEN BỜ SÔNG MÊ KÔNG L. Cuong & T. Tu https://doi.org/10.15625/1859-3097/16/4/9037
1234. Forecasting the number of sunspots for solar cycle 25 utilizing the facebook prophet model H. Rahman & W. Badawy https://doi.org/10.1038/s41598-025-33819-5
1235. Mapping and modelling land degradation vulnerability in a semi-arid region: a case study from Battalgazi District, Turkiye M. Kılıç https://doi.org/10.7717/peerj.20606
1236. Feature Selection Assists BLSTM for the Ultrasensitive Detection of Bioflavonoids in Different Biological Matrices Based on the 3D Fluorescence Spectra of Gold Nanoclusters H. Noreldeen et al. https://doi.org/10.1021/acs.analchem.2c03814
1237. Probabilistic prediction of stress–strain curves at the nanoscale: A multi-output Gaussian process approach with molecular dynamics simulations I. Altarabsheh et al. https://doi.org/10.1063/5.0250014
1238. Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions D. Rativa et al. https://doi.org/10.1109/JTEHM.2018.2797983
1239. A comparison of machine learning methods for predicting the compressive strength of field-placed concrete M. DeRousseau et al. https://doi.org/10.1016/j.conbuildmat.2019.08.042
1240. Methoxy and methylthio-substituted trans-stilbene derivatives as CYP1B1 inhibitors – QSAR study with detailed interpretation of molecular descriptors N. Piekuś-Słomka et al. https://doi.org/10.1016/j.arabjc.2022.104204
1241. Ethanol production from acid-pretreated and detoxified tea processing waste and its modeling M. Germec & I. Turhan https://doi.org/10.1016/j.fuel.2018.05.070
1242. Rainfall DSD Modelling Using Supervised Learning Techniques for Rain Attenuation Prediction in South Africa T. Ramatladi & A. Alonge https://doi.org/10.2528/PIERB25080106
1243. Wavelet-Based precipitation preprocessing for improved drought Forecasting: A Machine learning approach using tunable Q-factor wavelet transform and maximal overlap discrete wavelet transform S. Osmani et al. https://doi.org/10.1016/j.eswa.2024.124962
1244. Adaptive Neuro-Fuzzy Inference System to Predict the Release of Microplastic Fibers during Domestic Washing L. Muthusamy et al. https://doi.org/10.1520/JTE20210175
1245. Ensemble Machine Learning for Comprehensive Drought Assessment: A Case Study in the Mun Watershed of Northeast Thailand T. Phoophiwfa et al. https://doi.org/10.1134/S1995080225604953
1246. Daily rainfall estimates considering seasonality from a MODWT-ANN hybrid model E. Gomes & C. Blanco https://doi.org/10.2478/johh-2020-0043
1247. Groundwater recharge estimation in semi-arid zone: a study case from the region of Djelfa (Algeria) S. Ali Rahmani et al. https://doi.org/10.1007/s13201-016-0399-y
1248. Assessing simulation-based supervised machine learning for demographic parameter inference from genomic data A. Quelin et al. https://doi.org/10.1038/s41437-025-00773-x
1249. Prediction of Snatch and Clean and Jerk Performance From Physical Performance Measures in Elite Male Weightlifters I. Sandau & K. Kipp https://doi.org/10.1519/JSC.0000000000004945
1250. Parameter Estimation of Autoregressive-Exogenous and Autoregressive Models Subject to Missing Data Using Expectation Maximization M. Horner et al. https://doi.org/10.3389/fbuil.2019.00109
1251. Binary Grey Wolf Optimization-Regularized Extreme Learning Machine Wrapper Coupled with the Boruta Algorithm for Monthly Streamflow Forecasting J. Qu et al. https://doi.org/10.1007/s11269-021-02770-1
1252. Effects of distance and number of $$\hbox {PM}_{2.5}$$ low-cost sensors on correction models V. Kumar et al. https://doi.org/10.1007/s41060-025-00852-6
1253. Analyzing the Effects of Plasma Treatment Process Parameters on Fading of Cotton Fabrics Dyed with Two-Color Mix Dyes Using Bayesian Regulated Neural Networks (BRNNs) S. Liu et al. https://doi.org/10.1080/15440478.2023.2259101
1254. A novel physical process-ensemble learning model framework with residual error decomposition to upskill daily runoff prediction Y. Kang et al. https://doi.org/10.1016/j.jhydrol.2024.132565
1255. Optimization of Fly ash-slag based geopolymer strength, cost, and carbon emissions using CNN-based RSM and NSGA-III X. Kong et al. https://doi.org/10.1016/j.conbuildmat.2025.144380
1256. Prediction of NOx emissions from gas turbines of a combined cycle power plant using an ANFIS model optimized by GA M. Dirik https://doi.org/10.1016/j.fuel.2022.124037
1257. Estimating Carbon Dioxide Solubility in Brine Using Mixed Effects Random Forest Based on Genetic Algorithm: Implications for Carbon Dioxide Sequestration in Saline Aquifers G. Mwakipunda et al. https://doi.org/10.2118/223123-PA
1258. Application of Structural Equation Modeling (SEM) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Assessment of Safety Culture: An Integrated Modeling Approach E. Çakıt et al. https://doi.org/10.3390/safety6010014
1259. Data-driven prediction for curved pipe jacking performance during underwater excavation of ancient shipwreck using an attention-based graph convolutional network approach Z. Dai et al. https://doi.org/10.1016/j.eswa.2023.121393
1260. A qualitative analysis method for UV Raman spectra of domain - adaptive deep convolutional neural network X. Wang et al. https://doi.org/10.1088/1402-4896/add96d
1261. Modelling vegetation land fragmentation in urban areas of Western Province, Sri Lanka using an Artificial Intelligence-based simulation technique A. Jayasinghe et al. https://doi.org/10.1371/journal.pone.0275457
1262. Machine Learning Pipeline for Energy and Environmental Prediction in Cold Storage Facilities N. Alkhulaifi et al. https://doi.org/10.1109/ACCESS.2024.3482572
1263. Intelligent inverse design of hydrogen‑blended natural gas pipelines: coupling CFD simulations with machine learning optimization M. Wang et al. https://doi.org/10.1016/j.fuel.2026.140635
1264. Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy, USA S. Heddam https://doi.org/10.1007/s11356-016-6905-9
1265. A Decentralized Framework for Parameter and State Estimation of Infiltration Processes S. Bo & J. Liu https://doi.org/10.3390/math8050681
1266. Intelligent Analysis and Optimization of Lubrication Status Factor Based on Dynamically Loaded Roll Gap in Cold Strip Rolling S. Jin et al. https://doi.org/10.3390/lubricants13020054
1267. Location prediction algorithm for a nonlinear vehicular movement in VANET using extended Kalman filter R. Jaiswal & C. Jaidhar https://doi.org/10.1007/s11276-016-1265-4
1268. Stochastic Grey Wolf Optimization for Hyperparameter Tuning of LSTM and RNN Models in Energy Forecasting O. Albser et al. https://doi.org/10.1038/s41598-026-56787-w
1269. Generative Adversarial Networks Assist Missing Data Imputation: A Comprehensive Survey and Evaluation R. Shahbazian & S. Greco https://doi.org/10.1109/ACCESS.2023.3306721
1270. Contraste de análisis de frecuencias entre las distribuciones beta-kappa y beta-Pareto con tres de aplicación generalizada D. Campos-Aranda https://doi.org/10.24850/j-tyca-15-02-09
1271. Effect of substrate layers on thermo-electric performance under transient heat loads A. Rezania & E. Yazdanshenas https://doi.org/10.1016/j.enconman.2020.113068
1272. An Automated Method for Dual T2 Cutoff Determination and Permeability Prediction in Fine-Grained Hydrate-Bearing Sediments S. Shi et al. https://doi.org/10.1021/acs.energyfuels.5c06059
1273. Multi-objective aerodynamic optimization of ride height and rake angle in a sedan using CFD and machine learning M. Kheirkhah et al. https://doi.org/10.1016/j.taml.2026.100716
1274. Predicting outcomes of smoking cessation interventions in novel scenarios using ontology-informed, interpretable machine learning J. Hastings et al. https://doi.org/10.12688/wellcomeopenres.20012.1
1275. Comparison of eight filter-based feature selection methods for monthly streamflow forecasting – Three case studies on CAMELS data sets K. Ren et al. https://doi.org/10.1016/j.jhydrol.2020.124897
1276. A Subspace-Based Method for Facial Image Editing N. Yang et al. https://doi.org/10.1109/TCSS.2024.3447692
1277. Investigating ocean deoxygenation and the oxygen minimum zone in the Central Indo Pacific region based on the hindcast datasets K. Triana et al. https://doi.org/10.1007/s10661-022-10615-6
1278. LONG-TERM AIR QUALITY (PM2.5) PREDICTION USING DEEP LEARNING-BASED TEMPORAL CONVOLUTIONAL NETWORKS V. Doğan et al. https://doi.org/10.21923/jesd.1902759
1279. Threshold contour production of rainfall intensity that induces landslides in susceptible regions of northern Turkey O. Althuwaynee et al. https://doi.org/10.1007/s10346-018-0968-2
1280. Insights into machine-learning modeling for Cr(VI) removal from contaminated water using nano-nickel hydroxide I. Maamoun et al. https://doi.org/10.1016/j.seppur.2022.122863
1281. An energy-efficient knowledge discovery in cognitive IoT V. Jha & P. Tripathi https://doi.org/10.1007/s12597-025-00977-z
1282. Advanced machine learning-based kharif maize evapotranspiration estimation in semi-arid climate M. Jatav et al. https://doi.org/10.2166/wst.2023.253
1283. In situ calibration of an uncooled thermal camera for the accurate quantification of flower and stem surface temperatures R. Byerlay et al. https://doi.org/10.1016/j.tca.2020.178779
1284. Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model J. Brown et al. https://doi.org/10.1371/journal.pclm.0000295
1285. Can Decomposition Approaches Always Enhance Soft Computing Models? Predicting the Dissolved Oxygen Concentration in the St. Johns River, Florida M. Zounemat-Kermani et al. https://doi.org/10.3390/app9122534
1286. A Survey of Deep Learning for Time Series Forecasting: Theories, Datasets, and State-of-the-Art Techniques G. Lu et al. https://doi.org/10.32604/cmc.2025.068024
1287. Development of an intraoperative acoustic lung monitoring system for real-time respiratory rate detection in patient receiving mechanical ventilation K. Kang et al. https://doi.org/10.1007/s13534-025-00527-y
1288. Aphasia severity prediction using a multi-modal machine learning approach X. Hu et al. https://doi.org/10.1016/j.neuroimage.2025.121300
1289. Post-Translocation Establishment of the Endemic Cyprinid Squalidus multimaculatus Under Favorable Biogeochemical Conditions and Regional Winter Warming S. Choi et al. https://doi.org/10.3390/biology15141140
1290. Morphometric and physical characteristics of Indonesian beef cattle Y. Adinata et al. https://doi.org/10.5194/aab-66-153-2023
1291. Forecasting Brazil’s Energy Matrix Evolution: A Multi-Method Approach to Evaluate Alignment with SDG 7.2 H. Pimentel Tavares & E. da Silva Christo https://doi.org/10.5772/geet.20250064
1292. Modeling wetted areas of moisture bulb for drip irrigation systems: An enhanced empirical model and artificial neural network B. Karimi et al. https://doi.org/10.1016/j.compag.2020.105767
1293. Soil organic carbon modeling in cropland under several climatic scenarios using machine learning in western India A. Adeel et al. https://doi.org/10.1038/s41598-026-35191-4
1294. Laundry water reclamation using sustainable ceramic membrane from waste marble dust: Performance, fouling analysis H. Vaidhya et al. https://doi.org/10.1016/j.envres.2026.124624
1295. A comparative study of centrifugal fertilizer spread using generalized additive model, random forest and polynomial regression A. Lak et al. https://doi.org/10.1007/s11119-026-10366-1
1296. ULUSAL ELEKTRİK TÜKETİMİNİN MAKİNE ÖĞRENMESİ YÖNTEMLERİYLE TAHMİN EDİLMESİ: BİRLEŞİK KRALLIK VERİLERİYLE BİR UYGULAMA N. Ertoy & M. Akansel https://doi.org/10.17482/uumfd.1675895
1297. Mandated CSR spending and Tax aggressiveness: A machine learning-driven analysis A. Bhattacharyya & T. Imam https://doi.org/10.1016/j.jclepro.2024.142140
1298. Suitability of satellite-based rainfall products for estimating rainfall erosivity in areas with contrasted climate and terrain properties: Example of west-central Morocco N. Ben Daoud et al. https://doi.org/10.1007/s12040-024-02287-2
1299. Assessment of Aircraft Fuel Efficiency in Domestic Flights using Multiple Regression Analysis E. Sertdemir et al. https://doi.org/10.30518/jav.1662031
1300. Geospatial Analysis of Flood Hazard Using GIS-Based Hydrologic–Hydraulic Modeling: A Case of the Cagayan River Basin, Philippines W. Calapini et al. https://doi.org/10.3390/geomatics5040064
1301. Correcting the distortion of apparent resistivity pseudosection produced by 3D effect of the embankment geometry T. Nguyen & K. Pham https://doi.org/10.1007/s12665-018-7282-0
1302. Application of soft computing techniques for estimating emotional states expressed in Twitter® time series data E. Çakıt et al. https://doi.org/10.1007/s00521-019-04048-5
1303. Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures R. Hunt et al. https://doi.org/10.1177/20416695221116652
1304. Downscaling of Open Coarse Precipitation Data through Spatial and Statistical Analysis, Integrating NDVI, NDWI, Elevation, and Distance from Sea H. Ezzine et al. https://doi.org/10.1155/2017/8124962
1305. CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning From Sporadic Temporal Data M. Ghazi et al. https://doi.org/10.1109/TNNLS.2022.3177366
1306. Can machine learning predict PTSD symptoms from trauma narratives of children and adolescents? A. Giuliani et al. https://doi.org/10.1080/20008066.2025.2589709
1307. Machine-Learning Model for Predicting Maintenance Costs of EPDM Roofing Systems M. Alashari et al. https://doi.org/10.1061/JPCFEV.CFENG-4413
1308. The evaluation of accuracy and uniformity in the mass valuation of properties in the city of Johannesburg, South Africa S. Ngubeni et al. https://doi.org/10.1108/PM-02-2026-0025
1309. Application of Intelligent Recommendation for Agricultural Information: A Systematic Literature Review C. Song & H. Dong https://doi.org/10.1109/ACCESS.2021.3127201
1310. Fixed-volume multi-objective combustion chamber optimization for a compact UAV diesel engine based on an automatic intelligent optimization framework Q. Ma et al. https://doi.org/10.1016/j.energy.2026.142496
1311. Optimization approach to retrieve soil surface parameters from single-acquisition single-configuration SAR data A. Ghorbanian et al. https://doi.org/10.1016/j.crte.2018.11.005
1312. Identifying causes of errors between two wave-related data using performance metrics T. Iida https://doi.org/10.1016/j.apor.2024.104024
1313. Precipitation Data Accuracy and Extreme Rainfall Detection for Flood Risk Analysis in the Akçay Sub-Basin V. Lakshmi et al. https://doi.org/10.3390/rs17183199
1314. AI-driven carotid artery compressibility assessment via point-of-care ultrasound for blood pressure estimation in critically ill and post-resuscitation patients: a prospective observational study S. Maeng et al. https://doi.org/10.1186/s13054-025-05772-2
1315. Development of a Machine Learning–Based VO 2 max Prediction Framework Integrating Missing Data Imputation and SHAP Interpretation J. Lee & C. Kim https://doi.org/10.1080/15366367.2026.2669159
1316. Predicting intensity of white-tailed deer herbivory in the Central Appalachian Mountains A. Kniowski & W. Ford https://doi.org/10.1007/s11676-017-0476-6
1317. Sensitivity of WRF Rainfall Simulations to Physical Parameterization Schemes over Tropical Peatlands in the Maritime Continent M. Haikal et al. https://doi.org/10.1007/s13143-026-00454-7
1318. Machine Learning Powered Player Performance Prediction in Pro Baseball for Strategic Operations Y. Kim et al. https://doi.org/10.56977/jicce.2026.24.1.18
1319. Shallow Foundation Settlement Quantification: Application of Hybridized Adaptive Neuro‐Fuzzy Inference System Model M. Mohammed et al. https://doi.org/10.1155/2020/7381617
1320. Effect of geographical parameters on PM10 pollution in European landscapes: a machine learning algorithm-based analysis S. Sohrab et al. https://doi.org/10.1186/s12302-024-00972-z
1321. A systematic literature review of machine learning and deep learning for urban heat island modelling N. Samad et al. https://doi.org/10.1007/s44327-026-00223-1
1322. Electrical response of thermoelectric generator to geometry variation under transient thermal boundary condition E. Yazdanshenas et al. https://doi.org/10.1063/1.5040166
1323. Reverse survival model (RSM): a pipeline for explaining predictions of deep survival models M. Rezaei et al. https://doi.org/10.1007/s10489-023-04577-6
1324. Machine learning-driven prediction of halogen-tuned multifunctional properties in CsBX3 halide perovskites M. Jamal et al. https://doi.org/10.1016/j.physb.2026.419047
1325. Electrical Resistivity Imaging and the Saline Water Interface in High-Quality Coastal Aquifers A. Costall et al. https://doi.org/10.1007/s10712-018-9468-0
1326. Enhancing Socioeconomic Status Prediction for Cavities: A Hybrid Method A. Dao et al. https://doi.org/10.1177/00220345251324494
1327. A data-driven integrated framework for sustainable evaluation of grey–green urban drainage strategies under rainfall variability: Hydrodynamic surrogate modelling and economic assessment D. Méndez et al. https://doi.org/10.1016/j.jenvman.2026.129927
1328. Assessment of explainable tree-based ensemble algorithms for the enhancement of Copernicus digital elevation model in agricultural lands C. Okolie et al. https://doi.org/10.1080/19479832.2024.2329563
1329. AI-Driven Digital Twin for Optimizing Solar Submersible Pumping Systems Y. Salah et al. https://doi.org/10.3390/inventions10060093
1330. Novel Hopfield Neural Network Model with Election Algorithm for Random 3 Satisfiability M. Bazuhair et al. https://doi.org/10.3390/pr9081292
1331. Conscious points and patterns extraction: a high-performance computing model for knowledge discovery in cognitive IoT V. Jha & P. Tripathi https://doi.org/10.1007/s11227-024-06348-7
1332. Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece) S. Stefanidis & D. Stathis https://doi.org/10.3390/cli6030075
1333. Deciphering environmental determinants of soil metals in dust-influenced arid soils through interpretable models across data-availability scenarios Z. Ebrahimi-Khusfi et al. https://doi.org/10.1016/j.jenvman.2026.129472
1334. COVID-19 Vakalarının Makine Öğrenmesi Algoritmaları ile Tahmini: Amerika Birleşik Devletleri Örneği N. ÖZEN et al. https://doi.org/10.31590/ejosat.855113
1335. Contextual prediction of parking spot availability: A step towards sustainable parking G. Jelen et al. https://doi.org/10.1016/j.jclepro.2021.127684
1336. Performance Evaluation of Bias Correction Methods for Climate Change Monthly Precipitation Projections over Costa Rica M. Mendez et al. https://doi.org/10.3390/w12020482
1337. Meteorological Downscaling with WRF Model, Version 4.0, and Comparative Evaluation of Planetary Boundary Layer Schemes over a Complex Coastal Airshed C. Onwukwe & P. Jackson https://doi.org/10.1175/JAMC-D-19-0212.1
1338. A machine learning approach for the analysis of electron capture rates of A = 21–60 M. Hassani et al. https://doi.org/10.1140/epjp/s13360-026-07912-1
1339. Diagnosing global soil organic carbon mapping discrepancies with interpretable machine learning: A comparison of soil type linkage and digital soil mapping G. Shi et al. https://doi.org/10.1016/j.geoderma.2026.117998
1340. Befriend GenAI Chatbots: Exploring the Determinants of Parasocial Relationship in human-AI Interaction Through a Hybrid PLS-ANN-NCA Approach W. Zhong & J. Luo https://doi.org/10.1080/10447318.2025.2537794
1341. FLORA: a hierarchical fuzzy system for online accommodation review analysis T. Angskun & J. Angskun https://doi.org/10.1108/JSIT-03-2018-0046
1342. Deriving Coastal Shallow Bathymetry from Sentinel 2-, Aircraft- and UAV-Derived Orthophotos: A Case Study in Ligurian Marinas L. Apicella et al. https://doi.org/10.3390/jmse11030671
1343. ANN‐PID based automatic braking control system for small agricultural tractors N. Pradhan et al. https://doi.org/10.1002/rob.22393
1344. Remote Parkinson's disease severity prediction based on causal game feature selection Z. Xue et al. https://doi.org/10.1016/j.eswa.2023.122690
1345. Explainable ensemble machine learning framework for pavement concrete compressive strength and chloride ion penetration prediction Y. Yami et al. https://doi.org/10.1080/10298436.2026.2745035
1346. Introduction of the potential scour intensity (PSI) index for downstream scour assessment: FLOW-3D CFD simulations and experimental validation for slotted flip buckets P. Haghighatjou & G. Shams https://doi.org/10.1007/s40808-026-02807-7
1347. Enhancing Soft Tissue Differentiation with Different Dual-Energy CT Systems: A Phantom Study P. Gallo et al. https://doi.org/10.3390/app14051724
1348. Hybrid ML models for task-failure prediction on google cluster traces D. Shahmirzadi et al. https://doi.org/10.1007/s00607-026-01718-w
1349. Comparison between methods to predict climate change impacts on tropical shallow lakes L. Amorim et al. https://doi.org/10.2166/wcc.2023.100
1350. Accurate Terrain Modeling After Dark: Evaluating Nighttime Thermal UAV-Derived DSMs N. Polat et al. https://doi.org/10.3390/drones9060430
1351. Carbon Emission Prediction Model for Railway Passenger Stations on the Qinghai–Tibet Plateau G. Jia & Q. Wang https://doi.org/10.3390/su18083881
1352. Modelling Impacts of Climate Change and Anthropogenic Activities on Ecosystem State Variables of Water Quality in the Cat Ba–Ha Long Coastal Area (Vietnam) N. Hai et al. https://doi.org/10.3390/w17030319
1353. Predicting Blast-Induced Air Overpressure: A Robust Artificial Intelligence System Based on Artificial Neural Networks and Random Forest H. Nguyen & X. Bui https://doi.org/10.1007/s11053-018-9424-1
1354. Using APSIM Model to Optimize Nitrogen Application for Alfalfa Yield Under Different Precipitation Regimes Y. Wang et al. https://doi.org/10.3390/agriculture15161789
1355. Application of mathematical models to ethanol fermentation in biofilm reactor with carob extract M. Germec et al. https://doi.org/10.1007/s13399-019-00425-1
1356. A Stacked Regression Framework for Remaining Driving Range Estimation in Electric Two-Wheelers A. Amin https://doi.org/10.3390/wevj17060294
1357. A Comparative and Regional Study of Atmospheric Temperature in the Near-Space Environment Using Intelligent Modeling Z. Li et al. https://doi.org/10.3390/forecast8010001
1358. Reconstructing Soft Robotic Touch via In‐Finger Vision N. Guo et al. https://doi.org/10.1002/aisy.202400022
1359. A new disparity map quality assessment based on structural similarity for remotely sensed image pairs Q. Jia et al. https://doi.org/10.1080/2150704X.2020.1752409
1360. Applying Particle Swarm Optimization on VES Data for Groundwater Evaluation I. Khan et al. https://doi.org/10.32389/JEEG24-003
1361. Application of a Transfer Learning Model Combining CNN and Self-Attention Mechanism in Wireless Signal Recognition W. Wei et al. https://doi.org/10.3390/s25134202
1362. Identifying Soil and Plant Nutrition Factors Affecting Yield in Irrigated Mature Pistachio Orchards I. Esfandiarpour-Borujeni et al. https://doi.org/10.1080/00103624.2018.1464186
1363. Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model T. Gemechu et al. https://doi.org/10.3390/rs16213924
1364. Ultrasonic imaging of near-surface blind defects based on WSAttnGAN network Y. Xing et al. https://doi.org/10.1016/j.measurement.2024.116577
1365. Leveraging machine learning for accurate near-surface air temperature prediction to enhance climate adaptation in Ghana C. Oduro et al. https://doi.org/10.1016/j.jafrearsci.2025.105877
1366. Predicting mechanical properties of bainitic rail steels based on microstructure digitalization and machine learning L. Bai et al. https://doi.org/10.1016/j.jmrt.2025.01.155
1367. Pattern-prediction-based calibration of parametric point spread functions for advanced curvilinear extreme ultraviolet masks C. Liu et al. https://doi.org/10.35848/1347-4065/ae94ca
1368. Variability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Data M. Mammel et al. https://doi.org/10.3390/rs14122932
1369. The use of non-invasive fluorescence spectroscopy to quantify phenolic content under red wine real-time fermentation conditions I. dos Santos et al. https://doi.org/10.1016/j.foodcont.2023.109616
1370. FDPR: A Novel Fog Data Prediction and Recovery Using Efficient DL in IoT Networks M. Putra et al. https://doi.org/10.1109/JIOT.2023.3271026
1371. Optimizing buckling load of sandwich plates with cutouts using artificial neural networks and genetic algorithms M. Zeinali et al. https://doi.org/10.1080/15397734.2023.2272679
1372. Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks A. Manito et al. https://doi.org/10.3390/en11123303
1373. Enhancing Lake Tanganyika water level prediction using a hybrid ARIMA-SSA-LSTM and cluster-based analysis, East Africa A. Niyongabo et al. https://doi.org/10.2166/nh.2026.123
1374. LAI-Based Phenological Changes and Climate Sensitivity Analysis in the Three-River Headwaters Region X. Dai et al. https://doi.org/10.3390/rs14153748
1375. Global-scale comparison of OLCI remote sensing reflectance from sentinel-3A and -3B F. Mélin et al. https://doi.org/10.1016/j.rse.2026.115479
1376. Evaluation of fracture toughness properties of polymer concrete composite using deep learning approach M. Niaki et al. https://doi.org/10.1111/ffe.13889
1377. Assessing the spatial distribution of odor at an urban waterfront using AERMOD coupled with sensor measurements H. Zong et al. https://doi.org/10.1080/10962247.2023.2290710
1378. Multivariate Resource Usage Prediction With Frequency-Enhanced and Attention-Assisted Transformer in Cloud Computing Systems J. Bi et al. https://doi.org/10.1109/JIOT.2024.3395610
1379. GICL: A Cross-Modal Drug Property Prediction Framework Based on Knowledge Enhancement of Large Language Models N. Li et al. https://doi.org/10.1021/acs.jcim.5c00895
1380. Sentiment analysis methods, applications, and challenges: A systematic literature review Y. Mao et al. https://doi.org/10.1016/j.jksuci.2024.102048
1381. Research on Commodities Constraint Optimization Based on Graph Neural Network Prediction Z. Yang et al. https://doi.org/10.1109/ACCESS.2023.3302923
1382. Assessment of Climate-Driven Trends in Freeze-Up and Midwinter Breakups of Canadian River Ice Using a Multimodel Ensemble Framework M. De Coste https://doi.org/10.1061/JCRGEI.CRENG-1189
1383. A fully coupled atmosphere–ocean wave modeling system for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms P. Katsafados et al. https://doi.org/10.5194/gmd-9-161-2016
1384. Mapping the multidimensional structure–property landscape of polyolefin elastomers with interpretable machine learning H. Xu et al. https://doi.org/10.1016/j.polymer.2026.130607
1385. A Study on Accuracy of Meteorological Information for Low Altitude Aerospace around the Airport on the West Coast Y. Cho & K. Yoo https://doi.org/10.12985/ksaa.2020.28.2.053
1386. Predicting electronic stopping powers using stacking ensemble machine learning method F. Akbari et al. https://doi.org/10.1016/j.nimb.2023.02.023
1387. Fuzzy Mathematical Model of Photosynthesis in Jalapeño Pepper L. García-Rodríguez et al. https://doi.org/10.3390/agriculture14060909
1388. Integrating weather variables and AI models for forecasting major pests in jute: applications in climate-smart crop management P. Basak et al. https://doi.org/10.3389/fagro.2025.1687988
1389. Prediction of seakeeping in the early stage of conventional monohull vessels design using artificial neural network P. Romero-Tello et al. https://doi.org/10.1016/j.joes.2022.06.033
1390. Multilevel Rasch modeling of two-tier multiple choice test: A case study using Lawson’s classroom test of scientific reasoning Y. Xiao et al. https://doi.org/10.1103/PhysRevPhysEducRes.14.020104
1391. Large-Scale LoD2 Building Modeling using Deep Multimodal Feature Fusion F. Soleimani Vostikolaei & S. Jabari https://doi.org/10.1080/07038992.2023.2236243
1392. The new rheological model for zirconia suspensions with long-term kinetic stability P. Sokola et al. https://doi.org/10.1016/j.ceramint.2024.09.013
1393. Positional accuracy assessment of historical Google Earth imagery in Lagos State, Nigeria P. Nwilo et al. https://doi.org/10.1007/s12518-022-00449-9
1394. Modeling with Artificial Neural Networks to estimate daily precipitation in the Brazilian Legal Amazon E. Pinheiro Gomes et al. https://doi.org/10.1007/s00382-024-07200-7
1395. IoT Enabled Solar Powered Automation and Monitoring System for Modern Poultry Farming M. Hassain et al. https://doi.org/10.1007/s42979-026-05140-z
1396. On the accuracy of crop production and water requirement calculations: Process-based crop modeling at daily, semi-weekly, and weekly time steps for integrated assessments M. Ammar & E. Davies https://doi.org/10.1016/j.jenvman.2019.03.030
1397. Tanana River Test Site Model Verification Using the Marine and Hydrokinetic Toolkit (MHKiT) E. Browning et al. https://doi.org/10.3390/en16083326
1398. Hybrid vibro-acoustic model reduction for model updating in nuclear power plant pipeline with undetermined boundary conditions H. Shin et al. https://doi.org/10.1016/j.net.2024.03.046
1399. Machine learning-driven insights into the microstructure and properties of high-entropy alloys X. Zhang et al. https://doi.org/10.1016/j.apmate.2025.100331
1400. Comparative assessment of standalone and hybrid deep neural networks for modeling daily pan evaporation in a semi-arid environment M. Achite et al. https://doi.org/10.1038/s41598-025-05985-z
1401. A Machine Learning architecture to forecast Irregular Border Crossings and Asylum requests for policy support in Europe: a case study C. Bosco et al. https://doi.org/10.1017/dap.2024.48
1402. A Novel Comparative Statistical and Experimental Modeling of Pressure Field in Free Jumps along the Apron of USBR Type I and II Dissipation Basins S. Mousavi & D. Bocchiola https://doi.org/10.3390/math8122155
1403. Spatial Modeling of Potential Lobster Harvest Grounds in Palabuhanratu Bay, West Java, Indonesia M. Mukhtar et al. https://doi.org/10.3390/fishes6020016
1404. A double-loop framework reliability optimization method for electrical penetration assemblies in the reactor P. Yan et al. https://doi.org/10.1016/j.nucengdes.2025.114421
1405. Resolution Enhancement of SOHO/MDI Magnetograms Y. Qin et al. https://doi.org/10.1088/1674-4527/ad3b3b
1406. Estimation of Dilution Factor for Moving Cruise Ships by Artificial Neural Networks V. Şahin et al. https://doi.org/10.1007/s11270-022-05701-x
1407. A Transistor Operations Model for Deep Learning Energy Consumption Scaling Law C. Li et al. https://doi.org/10.1109/TAI.2022.3229280
1408. Comparative evaluation of machine learning models for extreme river water level forecasting in Bangladesh: Implications for flood and drought resilience M. Islam et al. https://doi.org/10.1016/j.pdisas.2025.100449
1409. Forecasting of electricity consumption in Pakistan based on integrating machine learning algorithms and Monte Carlo simulation M. Nazir & J. Li https://doi.org/10.1007/s00202-024-02923-6
1410. Nonlinear Model Identification Methodology for Small, Fixed-Wing, Unmanned Aircraft B. Simmons et al. https://doi.org/10.2514/1.C035160
1411. Generating soil salinity, soil moisture, soil pH from satellite imagery and its analysis M. Ghazali et al. https://doi.org/10.1016/j.inpa.2019.08.003
1412. Structural predictability differences in long-term regional crop yield modeling with climate and area signals M. Muhetaer et al. https://doi.org/10.1038/s41598-026-58313-4
1413. Anti-Interference DoA Estimation for LFM Radar Signals Using Space-Time-Modulated Metasurfaces J. Wu et al. https://doi.org/10.1109/TMTT.2024.3460106
1414. LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios A. Ahmed et al. https://doi.org/10.1007/s00477-021-01969-3
1415. Prediction of Compressive Strength of Concrete with Manufactured Sand by Ensemble Classification and Regression Tree Method Q. Ren et al. https://doi.org/10.1061/(ASCE)MT.1943-5533.0003741
1416. COVID-19 outbreak prediction using Seq2Seq + Attention and Word2Vec keyword time series data Y. Kim et al. https://doi.org/10.1371/journal.pone.0284298
1417. Multi-conformer molecules in solutions: an NMR-based DFT/MP2 conformational study of two glucopyranosides of a vitamin E model compound R. Nazarski et al. https://doi.org/10.1039/C5OB01865J
1418. On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow D. Tiwari et al. https://doi.org/10.5194/hess-28-1127-2024
1419. Experimental investigations and constitutive modeling of bitumen stabilized mixtures M. Nivedya et al. https://doi.org/10.1016/j.ijengsci.2016.02.008
1420. Computational analysis of L4–L5 interspinous process devices and interbody fusion spacers using ceramic and polymeric materials via finite element modeling and artificial intelligence Y. Shash & R. Elden https://doi.org/10.1038/s41598-025-20870-5
1421. Appearance and Pose-guided Human Generation: A Survey F. Liao et al. https://doi.org/10.1145/3637060
1422. An Improved Adaptive Iterative Extended Kalman Filter Based on Variational Bayesian Q. Fu et al. https://doi.org/10.3390/app14041393
1423. Terrestrial laser scanning-based allometric models for East-African tropical rainforest trees A. Mashera et al. https://doi.org/10.1016/j.tfp.2026.101211
1424. Hyperparameter-transfer learning framework for methane prediction in data-limited full-scale anaerobic digesters M. Kim et al. https://doi.org/10.1016/j.biortech.2026.135465
1425. Study on the Influence of Tunnel Fire Escape Situations on the Pressure of Fire Door 丹. 汪 https://doi.org/10.12677/mos.2025.145462
1426. Machine learning-based optimization of sustainable concrete mix for strength prediction S. Deb et al. https://doi.org/10.1007/s43621-026-03227-4
1427. A three-dimensional (3D) micro-potential-based peridynamics model for deformation and fracture in solid materials R. Liu et al. https://doi.org/10.1016/j.engfracmech.2023.109180
1428. Real-time warp and weft angle detection in fabrics using an oriented bounding box–based YOLOv8 deep learning model M. Sari et al. https://doi.org/10.1177/00405175261449432
1429. Optimal Time-Varying Vaccine Allocation Amid Pandemics With Uncertain Immunity Ratios S. Roy et al. https://doi.org/10.1109/ACCESS.2021.3053268
1430. Improving Satellite-Derived Bathymetry in Complex Coastal Environments: A Generalised Linear Model and Multi-Temporal Sentinel-2 Approach X. Monteys et al. https://doi.org/10.3390/rs17233834
1431. Mapping Between the Sydney Asthma Quality of Life Questionnaire (AQLQ-S) and Five Multi-Attribute Utility Instruments (MAUIs) B. Kaambwa et al. https://doi.org/10.1007/s40273-016-0446-4
1432. Validation of the CHIRPS and CPC-Unified products for estimating extreme daily precipitation over southwestern Iran H. Ghaedamini et al. https://doi.org/10.1007/s00704-021-03790-y
1433. Prediction of factor of safety of slopes using stochastically modified ANN and classical methods: a rigorous statistical model selection approach A. Lawal et al. https://doi.org/10.1007/s11069-023-06275-5
1434. Application of SWAN model for wave forecasting in the southern Baltic Sea supplemented with measurement and satellite data P. Sapiega et al. https://doi.org/10.1016/j.envsoft.2023.105624
1435. Modeling the relationship between maternal health and infant behavioral characteristics based on machine learning Z. Yang et al. https://doi.org/10.1371/journal.pone.0307332
1436. Unsupervised deep learning for 3D reconstruction with dual-frequency fringe projection profilometry S. Fan et al. https://doi.org/10.1364/OE.435606
1437. Improving Real-Time Flood Forecasting: Probabilistic Validation of Assimilated Remotely-Sensed Soil Moisture Data S. Soltani et al. https://doi.org/10.1007/s41748-025-00726-8
1438. Comparative Evaluation of Site Response Analysis Methods in Lima City: Case of the 2021 (Mw 6.0) Mala Earthquake C. Calderon et al. https://doi.org/10.20965/jdr.2025.p0886
1439. Novel occupancy detection method based on convolutional neural network model using PIR sensor and smart meter data Y. Wu et al. https://doi.org/10.1016/j.aei.2024.102589
1440. Vehicle-level multi-strategy benchmarking of NOx emission forecasting using integrated onboard and meteorological data A. Souza et al. https://doi.org/10.1038/s41598-026-57791-w
1441. Machine learning-based prediction of torsional behavior for ultra-high-performance concrete beams with variable cross-sectional shapes E. Khaoula et al. https://doi.org/10.1016/j.cscm.2024.e04136
1442. Optimal Identification of Concealed Copper Mineral Deposit Locations Utilising Isotope Signatures in Groundwater Systems R. Maharaj et al. https://doi.org/10.3390/w18192460
1443. AI-driven predictive and inverse design framework for defect engineering in hexagonal boron nitride monolayers S. Mousavi et al. https://doi.org/10.1016/j.matdes.2026.116542
1444. Enhancing Sensorless Speed Estimation Accuracy Through Global Parameter Identification and Neural Network-Based Residual Compensation M. Poyai et al. https://doi.org/10.3390/eng7080407
1445. A data-driven preference learning approach for multi-objective vehicle routing problems in last-mile delivery Z. Nourmohammadi et al. https://doi.org/10.1016/j.trc.2025.105101
1446. Using Geomorphological Indicators to Predict Earthquake Magnitude (MOb‒Max): A Case Study from Cao Bang Province and Adjasent Areas (Vietnam) C. Trong et al. https://doi.org/10.1134/S0016852122030104
1447. Evaluation of existing criteria in estimating shear strength of natural rock discontinuities H. Singh & A. Basu https://doi.org/10.1016/j.enggeo.2017.11.023
1448. Can DEM time series produced by UAV be used to quantify diffuse erosion in an agricultural watershed? N. Pineux et al. https://doi.org/10.1016/j.geomorph.2016.12.003
1449. Long-term daily prediction of saltwater intrusion based on the long memory-double autoregressive model K. Lin et al. https://doi.org/10.2166/hydro.2025.047
1450. Prediction for Overheating Risk Based on Deep Learning in a Zero Energy Building Y. Yuan et al. https://doi.org/10.3390/su12218974
1451. Lumped Approach for Reactive Transport of Organic Compound Mixtures through Simulated Aquifer Sands in Lab-Scale Column Tests J. Joo et al. https://doi.org/10.3390/w12113103
1452. Evaluation of the Relationship Between Escape Passage Length and Fire Door Pressure Difference D. Wang et al. https://doi.org/10.3390/fire9020055
1453. Non-singular terminal sliding mode control for redundantly actuated parallel mechanism H. Zhang et al. https://doi.org/10.1177/1729881420919548
1454. Comparative Analysis of Machine Learning Models for Chrysanthemum Growth M. Oh et al. https://doi.org/10.11623/frj.2025.33.2.07
1455. Regionalization of precipitation with determination of homogeneous regions via fuzzy c-means E. Gomes et al. https://doi.org/10.1590/2318-0331.231820180079
1456. Lineer ve Kübik Regresyon Analizleri Kullanılarak OECD Ülkelerinin CO2 Emisyonlarının Tahminlemesi E. GÜLER & S. YEREL KANDEMİR https://doi.org/10.31590/ejosat.1079187
1457. Laser Methane Emission Monitoring Based on Harmonic Ratio Feature and Estimation of Absorption Pulse Parameters N. Bach et al. https://doi.org/10.1134/S0020441225700526
1458. Predicting element concentrations by machine learning models in neutron activation analysis H. Nguyen et al. https://doi.org/10.1007/s10967-024-09424-7
1459. Improving vegetation photosynthesis model (VPM) by incorporating CO2 and atmospheric aerosols: A case study using urban and rural flux data from Shenzhen, China G. Dong et al. https://doi.org/10.1016/j.pce.2026.104430
1460. An Augmented Multiple Imputation Particle Filter for River State Estimation With Missing Observation Z. Ismail & N. Jalaludin https://doi.org/10.3389/frobt.2021.788125
1461. A novel hybrid TCN-TE-ANN model for high-precision solar irradiance prediction M. Isik https://doi.org/10.7717/peerj-cs.3026
1462. A heterogeneous traffic spatio-temporal graph convolution model for traffic prediction J. Xu et al. https://doi.org/10.1016/j.physa.2024.129746
1463. Data Driven Natural Gas Spot Price Prediction Models Using Machine Learning Methods M. Su et al. https://doi.org/10.3390/en12091680
1464. Estimating Solar Insolation and Power Generation of Photovoltaic Systems Using Previous Day Weather Data M. Chung & E. Brunesi https://doi.org/10.1155/2020/8701368
1465. Tail risk modelling of cryptocurrencies, gold, non-fungible token, and stocks Z. Barson & P. Owusu Junior https://doi.org/10.1016/j.resglo.2024.100229
1466. Validating NASA POWER meteorological data for applied climatology and agricultural modeling: a multi-decadal assessment across diverse topographies in the US and Türkiye H. Gürkan & G. Hoogenboom https://doi.org/10.1007/s00704-026-06532-0
1467. High-Dimensional Model Representation-Based Surrogate Model for Optimization and Prediction of Biomass Gasification Process Y. Ayub et al. https://doi.org/10.1155/2023/7787947
1468. Determination of moisture sorption isotherms of industrial hemp (Cannabis sativa L.) flower and leaf composite powders A. Oduola et al. https://doi.org/10.1016/j.indcrop.2022.115201
1469. Hematological picture of pediatric Sudanese patients with visceral leishmaniasis and prediction of leishmania donovani parasite load Z. Elnoor et al. https://doi.org/10.12998/wjcc.v12.i30.6374
1470. Data-Driven Framework for The Flow Characteristics of Self-Compacting Concrete Using Machine Learning https://doi.org/10.20900/jsr20260061
1471. Model predictive control (MPC) applied to a simplified model, magnetic nanoparticle hyperthermia (MNPH) treatment process M. Abu-Ayyad et al. https://doi.org/10.1088/2057-1976/ad460a
1472. Geospatial assessment of landslide-prone areas in the southern part of Anambra State, Nigeria using classical statistical models V. Nwazelibe & J. Egbueri https://doi.org/10.1007/s12665-024-11533-1
1473. Non-Gaussian Growth Dynamics of Stagonosporopsis cucurbitacearum: A Bayesian Analysis of Logistic Models M. de Lima et al. https://doi.org/10.1007/s13538-026-02052-4
1474. Performance Optimization of Expanded Polystyrene Lightweight Concrete Using a Multi-Objective Physically Interpretable Algorithm with Random Forest S. Li et al. https://doi.org/10.3390/buildings15213944
1475. Data-Driven Modeling of Lateral and Cracking Loads in Confined Masonry Walls Using Machine Learning H. Bile & K. Güler https://doi.org/10.3390/buildings14124016
1476. A case study on predicting groundwater quality in a drought-prone region of Vidarbha, Maharashtra using machine learning models B. Kumari et al. https://doi.org/10.1007/s13201-026-02866-2
1477. Augmented XGBoost modeling with CNN-extracted mass-spectral features and temporal embedding for enhanced prediction of pyrene degradation kinetics in advanced oxidation processes N. Liu et al. https://doi.org/10.1016/j.jece.2025.120704
1478. Application of the Orthogonal Polynomial Fitting Method in Estimating PM2.5 Concentrations in Central and Southern Regions of China B. Li et al. https://doi.org/10.3390/ijerph16081418
1479. Methodology for measuring dendrometric parameters in a mediterranean forest with UAVs flying inside forest R. Greco et al. https://doi.org/10.1016/j.jag.2023.103426
1480. Multimodal optimization: An effective framework for model calibration M. Chica et al. https://doi.org/10.1016/j.ins.2016.09.048
1481. Voice-Activated Smart Home Controller Using Machine Learning L. Filipe et al. https://doi.org/10.1109/ACCESS.2021.3076750
1482. A methodological framework for the global index of volunteer engagement (GIVE): Measuring volunteerism in official statistics S. Manda et al. https://doi.org/10.1177/18747655261486416
1483. Application of random number generators in genetic algorithms to improve rainfall-runoff modelling M. Chlumecký et al. https://doi.org/10.1016/j.jhydrol.2017.08.025
1484. Deep learning-based superconductivity prediction and experimental tests D. Kaplan et al. https://doi.org/10.1140/epjp/s13360-024-05947-w
1485. Updated Lagrangian Particle Hydrodynamics (ULPH) Modeling of Natural Convection Problems J. Xiong et al. https://doi.org/10.32604/cmes.2024.053078
1486. Aerosol Optical Depth Over the Nepalese Cryosphere Derived From an Empirical Model B. Bhattarai et al. https://doi.org/10.3389/feart.2019.00178
1487. Event-based control of postoperative analgesia using physiological nociception signals B. Ayvaz et al. https://doi.org/10.1016/j.bspc.2026.110867
1488. Experimental investigation of predictive control for PMSM-based wind turbine generation system N. Nouraldin et al. https://doi.org/10.1016/j.compeleceng.2024.109554
1489. Modeling seasonal water status and predicting yield in almond orchards using UAV multi-sensor and meteorological data N. Efrat et al. https://doi.org/10.1016/j.agwat.2025.109868
1490. Assessment of Weather Research and Forecasting (WRF) Physical Schemes Parameterization to Predict Moderate to Extreme Rainfall in Poorly Gauged Basin S. Zaidi et al. https://doi.org/10.3390/su141912624
1491. A novel approach for the estimation of hydrological drought index incorporating precipitation-runoff relationship X. Li et al. https://doi.org/10.1016/j.jhydrol.2025.132734
1492. Blast Hazard Resilience Using Machine Learning for West Fertilizer Plant Explosion Z. Huang et al. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001644
1493. System Identification for Propellers at High Incidence Angles B. Simmons https://doi.org/10.2514/1.C036329
1494. Referencing acoustic monitoring of cutting knives sharpness in agricultural harvesting processes using image analysis H. Siebald et al. https://doi.org/10.1016/j.biosystemseng.2022.12.007
1495. Prediction of the performance of pre‐packed purification columns through machine learning Q. Jiang et al. https://doi.org/10.1002/jssc.202100864
1496. The practical design of a vehicle magnetic signature generator M. Stojanović et al. https://doi.org/10.1177/01423312221142557
1497. Water quality prediction using ARIMA-SSA-LSTM combination model T. Wang et al. https://doi.org/10.2166/ws.2024.060
1498. Sensitizing Netizen’s behavior through influencer intervention enabled by crowdsourcing – a case of reddit J. Yadav et al. https://doi.org/10.1080/0144929X.2021.1872705
1499. Novel dynamic thermal comfort prediction in buildings with single-shot vision-based deep learning method and low-cost thermographic imaging W. Zhang et al. https://doi.org/10.1016/j.buildenv.2025.113549
1500. Machine learning-driven reliability assessment of liquefaction probability based on state parameter analysis K. Kumar et al. https://doi.org/10.1016/j.jrmge.2025.07.034
1501. Feature learning and process monitoring of injection molding using convolution-deconvolution auto encoders T. Mao et al. https://doi.org/10.1016/j.compchemeng.2018.07.009
1502. Anisotropic dispersion with a consistent smoothed particle hydrodynamics scheme C. Alvarado-Rodríguez et al. https://doi.org/10.1016/j.advwatres.2019.07.004
1503. Evaluation of Global Gridded Precipitation and Temperature Datasets against Gauged Observations over the Upper Tekeze River Basin, Ethiopia K. Reda et al. https://doi.org/10.1007/s13351-021-0199-7
1504. Smart Urban Cadastral Map Enrichment—A Machine Learning Method A. Hajiheidari et al. https://doi.org/10.3390/ijgi13030080
1505. Application of machine learning techniques for obesity prediction: a comparative study M. Dirik https://doi.org/10.21595/chs.2023.23193
1506. Design and construction of a flexible laboratory-scale mixing apparatus for continuous ethylene supplementation of fresh produce R. Amoah et al. https://doi.org/10.1016/j.biosystemseng.2017.02.010
1507. RainPredRNN: A New Approach for Precipitation Nowcasting with Weather Radar Echo Images Based on Deep Learning D. Tuyen et al. https://doi.org/10.3390/axioms11030107
1508. Integrating Reflective Practice into the Self-Improvement Cycle Module for Renewable Energy Forecasting Accuracy G. Veigners et al. https://doi.org/10.2478/plua-2024-0012
1509. Strength estimation of concrete masonry units using stress-wave methods S. Sajid et al. https://doi.org/10.1016/j.conbuildmat.2017.12.044
1510. Development of deep neural network model to predict the compressive strength of FRCM confined columns K. Le-Nguyen et al. https://doi.org/10.1007/s11709-022-0880-7
1511. Robust parametric modeling of Alzheimer’s disease progression M. Mehdipour Ghazi et al. https://doi.org/10.1016/j.neuroimage.2020.117460
1512. Neural ordinary differential equations for learning and extrapolating system dynamics across bifurcations E. van Tegelen et al. https://doi.org/10.1063/5.0288264
1513. Machine learning-based estimation of chlorophyll-a in the Mississippi Sound using Landsat and ocean optics data H. Ahmad et al. https://doi.org/10.1007/s12665-025-12191-7
1514. Machine learning surrogate modelling for enhanced heat transfer in heat exchangers: A state-of-the-art review M. Zálešák et al. https://doi.org/10.1016/j.egyai.2026.100931
1515. Development of compressive strength prediction platform for concrete materials based on machine learning techniques K. Liu et al. https://doi.org/10.1016/j.jobe.2023.107977
1516. Application of feature selection and regression models for chlorophyll-a prediction in a shallow lake X. Li et al. https://doi.org/10.1007/s11356-018-2147-3
1517. Single channel high noise level ECG deconvolution using optimized blind adaptive filtering and fixed-point convolution kernel compensation M. Mohebbian et al. https://doi.org/10.1016/j.bspc.2019.101673
1518. Predicting intraurban PM2.5 concentrations using enhanced machine learning approaches and incorporating human activity patterns M. Ashayeri et al. https://doi.org/10.1016/j.envres.2020.110423
1519. Molecular Interactions and IR Spectral Insights in [Emim][Triflate] and 2-Alkoxyethanol Mixtures: Refractive Index Predictions Using Classical Theories and Machine Learning A. Munnangi et al. https://doi.org/10.1021/acs.jced.4c00601
1520. Above- and belowground tree biomass models for three mangrove species in Tanzania: a nonlinear mixed effects modelling approach M. Njana et al. https://doi.org/10.1007/s13595-015-0524-3
1521. Utilizing and Optimizing Forecasting Models for Nursing Demand: A Narrative Review K. Singh et al. https://doi.org/10.1002/hsr2.72046
1522. Improving accuracy of neuro fuzzy and support vector regression for drought modelling using grey wolf optimization A. Mirboluki et al. https://doi.org/10.1080/02626667.2022.2082877
1523. Machine learning-based projections of earth skin temperature anomalies in Nigeria using ERA5-land data M. Lateef et al. https://doi.org/10.1080/29966876.2026.2624855
1524. Transient three-dimensional CFD modelling of ceiling fans F. Babich et al. https://doi.org/10.1016/j.buildenv.2017.06.039
1525. Estimation and Classification of Coffee Plant Water Potential Using Spectral Reflectance and Machine Learning Techniques D. Delfino et al. https://doi.org/10.3390/biophysica5040060
1526. A Comparative Study of Deep Learning Models on Tropospheric Ozone Forecasting Using Feature Engineering Approach R. Rezaei et al. https://doi.org/10.3390/atmos14020239
1527. Prediction of HPC compressive strength based on machine learning L. Jin et al. https://doi.org/10.1038/s41598-024-67850-9
1528. Modeling uptake of nanoparticles in multiple human cells using structure–activity relationships and intercellular uptake correlations N. Basant & S. Gupta https://doi.org/10.1080/17435390.2016.1257075
1529. Recent Advances in Toxicity Prediction: Applications of Deep Graph Learning Y. Miao et al. https://doi.org/10.1021/acs.chemrestox.2c00384
1530. Foundations for pH control by moisture during cocoa fermentation is revealed by genetic and stepwise regression analysis R. Frimpomaa Udzu et al. https://doi.org/10.1080/23311932.2026.2651461
1531. Fuzzy inference optimization algorithms for enhancing the modelling accuracy of wastewater quality parameters T. Abunama et al. https://doi.org/10.1016/j.jenvman.2021.112862
1532. A predictive analytics framework for sensor data using time series and deep learning techniques H. Selmy et al. https://doi.org/10.1007/s00521-023-09398-9
1533. 基于边缘自先验和方向总变差的旋转CL图像重建算法 王. WANG Haoyu et al. https://doi.org/10.3788/gzxb20255410.1010001
1534. Load-carrying capacity and mode failure simulation of beam-column joint connection: Application of self-tuning machine learning model A. Alwanas et al. https://doi.org/10.1016/j.engstruct.2019.05.048
1535. End-to-end deep learning framework for automated angle estimation in hallux valgus from full-field weight-bearing radiographs Q. Wang et al. https://doi.org/10.1186/s12880-026-02150-4
1536. Using Monte-Carlo simulations to evaluate the efficiency of different strategies for nondestructive assessment of concrete strength M. Alwash et al. https://doi.org/10.1617/s11527-016-0962-x
1537. CBRL and CBRC: Novel Algorithms for Improving Missing Value Imputation Accuracy Based on Bayesian Ridge Regression S. M. Mostafa et al. https://doi.org/10.3390/sym12101594
1538. A network-based toolkit for evaluation and intercomparison of weather prediction and climate modeling C. Wang & Z. Wang https://doi.org/10.1016/j.jenvman.2020.110709
1539. P2O: AI-Driven Framework for Managing and Securing Wastewater Treatment Plants A. Kulkarni et al. https://doi.org/10.1061/JOEEDU.EEENG-7266
1540. Assessing the impacts of climate change on flooding under Coupled Model Intercomparison Project Phase 6 scenarios in the river Chenab, Pakistan S. Kiran et al. https://doi.org/10.1007/s11069-023-05892-4
1541. Leveraging Floating Car Data (FCD) for Traffic Forecasting in Sensorless Roads D. Pagano et al. https://doi.org/10.1016/j.trpro.2026.02.087
1542. Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration F. Concas et al. https://doi.org/10.1145/3446005
1543. SHAP based interpretable machine learning for predicting pressuremeter modulus from common geotechnical tests M. Arabani et al. https://doi.org/10.1016/j.rineng.2026.110979
1544. Immobilization of Cr(VI) in soil through injection of nanoscale FeII-AlIII LDH suspension into the soil column L. Alidokht et al. https://doi.org/10.1016/j.geoderma.2020.114648
1545. Estimating Residual Value of Heavy Construction Equipment Using Ensemble Learning I. Milošević et al. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002088
1546. Enhancing obsolescence forecasting with deep generative data augmentation: a semi-supervised framework for low-data industrial applications E. Saad et al. https://doi.org/10.1007/s10845-025-02746-7
1547. Forest Fire Monitoring and Positioning Improvement at Subpixel Level: Application to Himawari-8 Fire Products H. Xu et al. https://doi.org/10.3390/rs14102460
1548. Machine learning-based modeling of watershed drainage density in different climates K. Chapi et al. https://doi.org/10.1007/s40808-026-02819-3
1549. Examining the generalizability of inverse surrogate models for different geometries and locations L. Jowett-Lockwood & R. Evins https://doi.org/10.1016/j.enbuild.2025.115539
1550. Molecular modeling studies of 1,2,4-triazine derivatives as novel h-DAAO inhibitors by 3D-QSAR, docking and dynamics simulations P. Qian et al. https://doi.org/10.1039/C8RA00094H
1551. Credit scoring for a microcredit data set using the synthetic minority oversampling technique and ensemble classifiers A. Gicić & A. Subasi https://doi.org/10.1111/exsy.12363
1552. Evaluation of GRACE and GRACE-FO derived-products for water storage assessment in Moroccan aquifers: analysis of drought and human-induced impacts M. Abbad et al. https://doi.org/10.1080/10106049.2025.2521829
1553. H2O2 treatment enhanced the heavy metals removal by manure biochar in aqueous solutions Y. Wang & R. Liu https://doi.org/10.1016/j.scitotenv.2018.02.137
1554. Makine Öğrenmesi Modelleri ile Lamine Ahşap Kirişlerin Eğilme Dayanımı (MOR) Değerlerinin Tahmini İ. Kılıç et al. https://doi.org/10.70700/bjea.1816397
1555. Wheat yield prediction for sustainable food security using Sentinel-2 and machine learning N. Civelek et al. https://doi.org/10.51489/tuzal.1760511
1556. A Construction-Phase Reliability Framework for Hard Rock TBM Penetration Rate Prediction Under Delayed UCS Information N. Monthanopparat & T. Tanchaisawat https://doi.org/10.3390/geotechnics6030061
1557. Deep learning and optimisation for quality of service modelling K. Arunachalam et al. https://doi.org/10.1016/j.jksuci.2022.01.016
1558. Development of ground motion models using supervised learning: application to North and Northeast India A. Sankar & S. Kolathayar https://doi.org/10.1007/s10950-025-10354-4
1559. Optimizing simulation of summer precipitation by weather research and forecasting model over the mountainous southern Tibetan Plateau H. Liu et al. https://doi.org/10.1016/j.atmosres.2022.106484
1560. Spatial Analysis and Assessment of Relative Fire Risk Using Public Data D. Kim et al. https://doi.org/10.9798/KOSHAM.2026.26.4.173
1561. A hybrid approach for the spatial disaggregation of socio-economic indicators J. Monteiro et al. https://doi.org/10.1007/s41060-017-0080-z
1562. Morphodynamic predictions based on Machine Learning. Performance and limits for pocket beaches near the Bilbao port M. Viñes et al. https://doi.org/10.3389/fenvs.2025.1600473
1563. Analysis of Spatial and Temporal Criteria for Altimeter Collocation of Significant Wave Height and Wind Speed Data in Deep Waters R. Campos https://doi.org/10.3390/rs15082203
1564. Quality improvement in sand casting process: a hybrid approach based on machine learning and metaheuristic optimization methods Y. Çiçek & F. Gürbüz https://doi.org/10.1007/s10845-025-02698-y
1565. Kinetic modeling, sensitivity analysis, and techno-economic feasibility of ethanol fermentation from non-sterile carob extract-based media in Saccharomyces cerevisiae biofilm reactor under a repeated-batch fermentation process M. Germec et al. https://doi.org/10.1016/j.fuel.2022.124729
1566. Review of microclimate effects on PET and UTCI for developing outdoor adaptive models A. Gunadhi et al. https://doi.org/10.1016/j.rineng.2026.112624
1567. Recommendation System Algorithms on Location-Based Social Networks: Comparative Study A. Al-Nafjan et al. https://doi.org/10.3390/info13040188
1568. FeatureMF: An Item Feature Enriched Matrix Factorization Model for Item Recommendation H. Zhang et al. https://doi.org/10.1109/ACCESS.2021.3074365
1569. Improving Energy and Molecular Properties by Convergence of the One‐Particle Reduced Density Matrix in Variational Quantum Eigensolvers (VQE) A. de Lima et al. https://doi.org/10.1002/jcc.70289
1570. Enhancing Urban Ecological Risk Assessment by Integrating Spatial Modeling and Machine Learning for Resilient Environmental Management in UNESCO World Heritage Cities Z. Rahaman et al. https://doi.org/10.1007/s41748-024-00468-z
1571. Leaf area index (LAI) prediction using machine learning and UAV based vegetation indices S. Hussain et al. https://doi.org/10.1016/j.eja.2025.127557
1572. Multivariate vector autoregressive modelling of malaria with climate and vegetation factors in a remote hilly region of Northeast India A. Youroi et al. https://doi.org/10.1007/s10661-025-13962-2
1573. Data-Driven Approach for Predicting Gasoline Yield in an FCC Unit Charged with Light and Heavy Feedstocks: A PCA-Guided Grouping for Enhanced Modeling Experience K. Alelg et al. https://doi.org/10.1021/acs.jcim.5c02281
1574. 基于自注意力机制U-net的微焦CT去射线源模糊方法 刘. Liu Chuanjiang et al. https://doi.org/10.3788/AOS231855
1575. Hypergraph-based spiking neural P systems for predicting the overall survival time of glioblastoma patients J. Dai et al. https://doi.org/10.1016/j.eswa.2022.119234
1576. A predictive growth model of Staphylococcus aureus during temperature abuse conditions V. Juneja et al. https://doi.org/10.1016/j.foodres.2025.116032
1577. Non-metal content optimization strategy based on density functional theory and machine learning: Enhancing the hydrogen evolution reaction performance of metal-doped catalysts Z. Xiong et al. https://doi.org/10.1016/j.mtcomm.2025.113463
1578. Groundwater potential mapping in structurally complex karst aquifers: Comparing ANN, SVR, and ANN–SVR models in Khuzestan Province, southwestern Iran S. Pourmorad et al. https://doi.org/10.1016/j.gsd.2026.101652
1579. Developmental-Stage-Aligned Explainable Machine Learning Identifies Climate-Sensitive Windows and Conditional SOM-Related Buffering Patterns in Maize Growth in Western Liaoning, China J. Xu et al. https://doi.org/10.3390/agronomy16191918
1580. A machine learning approach to portfolio pricing and risk management for high‐dimensional problems L. Fernandez‐Arjona & D. Filipović https://doi.org/10.1111/mafi.12358
1581. Estimation of sea state parameters from ship motion responses using attention-based neural networks D. Selimović et al. https://doi.org/10.1016/j.oceaneng.2023.114915
1582. Methodology for the development of a new Sustainable Infrastructure Rating System for Developing Countries (SIRSDEC) J. Diaz-Sarachaga et al. https://doi.org/10.1016/j.envsci.2016.12.010
1583. Spatio-Temporal small area estimation of subdistrict per capita expenditure: Integrating panel survey and geospatial big data H. Zebua et al. https://doi.org/10.1177/18747655261435168
1584. A new hybrid multivariate prediction model based on wavelet transform convolution for PM2.5 prediction X. Lu et al. https://doi.org/10.1007/s44273-025-00067-y
1585. Validation and Verification of Computational Model for the Numerical Simulation of the Operational Principle of a Submerged Horizontal Plate Device G. Thum et al. https://doi.org/10.4028/p-rbUO0u
1586. Calibration method of vision measurement system for ceramic billet grinding robot S. Diao et al. https://doi.org/10.1049/joe.2018.5096
1587. Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees H. Ly et al. https://doi.org/10.3390/ma12091544
1588. A neural network model for solvency calculations in life insurance L. Fernandez-Arjona https://doi.org/10.1017/S1748499520000330
1589. APPLICATION OF HEURISTIC OPTIMIZATION APPROACHES TO EVALUATE COMPACTION PARAMETERS M. Rahman https://doi.org/10.36937/cebel.2025.1995
1590. Application of the empirical line method (ELM) to calibrate the airborne Daedalus-CZCS scanner L. Pompilio et al. https://doi.org/10.1080/22797254.2017.1399087
1591. Innovative MCDM-ML algorithms-based decision-support system for electric vehicle selection A. Şimşek et al. https://doi.org/10.1007/s10668-025-06476-x
1592. Machine learning prediction of the conversion of lignocellulosic biomass during hydrothermal carbonization N. Kardani et al. https://doi.org/10.1080/17597269.2021.1894780
1593. Predicting Energy Demand Using Machine Learning: Exploring Temporal and Weather-Related Patterns, Variations, and Impacts B. Sahin et al. https://doi.org/10.1109/ACCESS.2024.3370442
1594. 红外热图像的自然感彩色化质量评价方法 盛. Sheng Dian et al. https://doi.org/10.3788/AOS251016
1595. A hybrid deep learning approach for dynamic attitude and position prediction in tunnel construction considering spatio-temporal patterns X. Fu et al. https://doi.org/10.1016/j.eswa.2022.118721
1596. Mapping forest vegetation patterns in an Atlantic–Mediterranean transitional area by integration of ordination and geostatistical techniques A. Olthoff et al. https://doi.org/10.1093/jpe/rtw112
1597. Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties L. Kouadio et al. https://doi.org/10.1016/j.compag.2018.10.014
1598. Deciphering the field of uplift from landscape: A genetic algorithm‐based inversion method X. Zhao et al. https://doi.org/10.1002/esp.70266
1599. A profile shape correction to reduce the vertical sensitivity of cosmic‐ray neutron sensing of soil moisture L. Scheiffele et al. https://doi.org/10.1002/vzj2.20083
1600. Selective Separation of Calcium from Lithium in Synthetic Geothermal Brine Using Ion Exchange: Breakthrough Curve Analysis and Machine Learning Modeling Insights M. Musa et al. https://doi.org/10.1007/s40831-026-01541-9
1601. Data-driven approach for intelligent tunnel dust concentration prediction T. Yang et al. https://doi.org/10.1088/1755-1315/1337/1/012030
1602. Model reconstruction method of irregular columnar jointed rock masses and corresponding elastic parameter analysis S. Li et al. https://doi.org/10.1016/j.compgeo.2024.106932
1603. A Machine Learning Framework for the Reconstruction of Composite Fatigue and Fracture Properties: A Synthetic Data Study S. Tiwari & A. Gupta https://doi.org/10.3390/ma19061131
1604. Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability Y. Yu et al. https://doi.org/10.1016/j.uclim.2024.102003
1605. Hybrid ARIMAX–LSTM Modeling for Enhanced Vibration Prediction in Rotating Machinery: Application to a Cement Mill Fan N. Allassak et al. https://doi.org/10.48084/etasr.11845
1606. Statistical Learning for Predicting School Dropout in Elementary Education: A Comparative Study R. do Nascimento et al. https://doi.org/10.1007/s40745-021-00321-4
1607. Fine-Scale Identification of Deep Lithology and Potential Favorable Intervals in WWY1 Well, Wuwei Depression: Implications from Support Vector Machine Analysis of Multiparameter Logging Responses L. Teng et al. https://doi.org/10.3390/min16080828
1608. Is Noninvasive Brachial Systolic Blood Pressure an Accurate Estimate of Central Aortic Systolic Blood Pressure? Y. Shih et al. https://doi.org/10.1093/ajh/hpv164
1609. Remaining Useful Life Prediction of Cutting Tools Based on a Depthwise Separable TCN-BiLSTM Model with Temporal Attention S. Wang et al. https://doi.org/10.3390/lubricants13110507
1610. Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region S. Çadırcı & İ. Tekdemir https://doi.org/10.38088/jise.1635104
1611. Dimensionality reduction and prediction of soil consolidation coefficient using random forest coupling with Relief algorithm H. Ly et al. https://doi.org/10.1007/s11709-022-0812-6
1612. Salient Object Detection Based on Optimization of Feature Computation by Neutrosophic Set Theory S. Song et al. https://doi.org/10.3390/s23208348
1613. Prediction of morning fatigue severity in outpatients receiving chemotherapy: less may still be more K. Kober et al. https://doi.org/10.1007/s00520-023-07723-5
1614. From scalar indicators to full-field prediction: A multi-scale surrogate framework for thermal-field design in large-diameter Czochralski growth Z. Wang et al. https://doi.org/10.1016/j.jcrysgro.2026.128607
1615. Content Recommendation Algorithm for Intelligent Navigator in Fog Computing Based IoT Environment F. Lin et al. https://doi.org/10.1109/ACCESS.2019.2912897
1616. Hybrid soft computing approach for determining water quality indicator: Euphrates River J. Li et al. https://doi.org/10.1007/s00521-017-3112-7
1617. Exploring the synergy between nano-influencers and sports community: behavior mapping through machine learning J. Yadav et al. https://doi.org/10.1108/ITP-03-2021-0219
1618. Identifying key determinants of discharge capacity in ternary cathode materials of lithium-ion batteries X. Li et al. https://doi.org/10.1016/j.cclet.2024.109870
1619. Measurement of deformation of the concrete sleepers under different support conditions using non-contact laser speckle imaging sensor Y. Pang et al. https://doi.org/10.1016/j.engstruct.2019.110054
1620. ANN BASED EARLY DETECTION OF ALZHEIMER DISEASE ON SELECTED FEATURES S. YILDIZ & K. YILDIZ https://doi.org/10.21923/jesd.1296283
1621. Evaluation of the effect of high penetration of renewable energy sources (RES) on system frequency regulation using stochastic risk assessment technique (an approach based on improved cumulant) A. Habib et al. https://doi.org/10.1016/j.renene.2018.04.063
1622. Prediction of surface roughness in duplex stainless steel top milling using machine learning techniques G. Vasconcelos et al. https://doi.org/10.1007/s00170-024-14290-4
1623. Individual mangrove tree measurement using UAV-based LiDAR data: Possibilities and challenges D. Yin & L. Wang https://doi.org/10.1016/j.rse.2018.12.034
1624. EVAonline: An open-source web platform for global reference evapotranspiration estimation via multi-source data fusion A. Soares et al. https://doi.org/10.1016/j.envsoft.2026.107113
1625. Critical review on the application of artificial intelligence techniques in the production of geopolymer-concrete G. Alaneme et al. https://doi.org/10.1007/s42452-023-05447-z
1626. Public debt forecasts and machine learning: the Italian case E. Sica et al. https://doi.org/10.1108/JES-07-2023-0337
1627. The prediction of hydroxyapatite crystallinity under various ion doping using machine learning A. Pradana et al. https://doi.org/10.1016/j.rechem.2025.102701
1628. A Hybrid Neuro-Fuzzy Approach for Site-Specific Liquefaction Assessment Using Metaheuristic Tuning Techniques C. Kumari & A. Verma https://doi.org/10.1007/s40515-025-00703-8
1629. Explaining the Performance Hierarchy of Linear Regression, Support Vector Regression, and Random Forest on Physics-Generated PVT Data: A Real-Gas-Law and Gauss-Markov Perspective G. Hie et al. https://doi.org/10.4236/ojg.2026.169029
1630. Multimodal Particulate Matter Prediction: Enabling Scalable and High-Precision Air Quality Monitoring Using Mobile Devices and Deep Learning Models H. Madokoro & S. Nix https://doi.org/10.3390/s25134053
1631. Modeled associations between university physical education mechanisms and students’ mental health R. Zhu et al. https://doi.org/10.3389/fpsyg.2026.1829590
1632. Application of soft computing techniques in tunnelling and underground excavations: state of the art and future prospects S. Shreyas & A. Dey https://doi.org/10.1007/s41062-019-0234-z
1633. CRISPR-FMC: a dual-branch hybrid network for predicting CRISPR-Cas9 on-target activity C. Li et al. https://doi.org/10.3389/fgeed.2025.1643888
1634. Internet of Things (IoT) for Soil Moisture Detection Using Time Series Model I. Setiawan et al. https://doi.org/10.15575/join.v7i2.951
1635. Development and field based validation of a predictive model for concrete compressive strength using fresh state properties in a large scale construction project G. Solano-Vinueza & J. Albuja-Sánchez https://doi.org/10.1016/j.cscm.2025.e05705
1636. Reality mining and predictive analytics for building smart applications H. Asri et al. https://doi.org/10.1186/s40537-019-0227-y
1637. Reanalysis profile downscaling with WRF model and sensitivity to PBL parameterization schemes over a subtropical station L. Diaz et al. https://doi.org/10.1016/j.jastp.2021.105724
1638. Optimized Gaussian Process Regression for Multimodal Spatio-Temporal Prediction of Alzheimer's Disease Progression M. Harahap et al. https://doi.org/10.48084/etasr.16367
1639. Data-driven catalyst–process optimization of the water–gas shift reaction using an interpretable TabPFN–ensemble framework Y. Kim et al. https://doi.org/10.1016/j.jiec.2026.06.008
1640. Partial purification and characterization of a recombinant β-mannanase from Aspergillus fumigatus expressed in Aspergillus sojae grown on carob extract E. Karahalil et al. https://doi.org/10.1007/s13399-019-00487-1
1641. Reliability of MyotonPro in measuring the biomechanical properties of the quadriceps femoris muscle in people with different levels and types of motor preparation R. Trybulski et al. https://doi.org/10.3389/fspor.2024.1453730
1642. Assessment of the Baspa basin glaciers mass budget using different remote sensing methods and modeling techniques V. Gaddam et al. https://doi.org/10.1080/10106049.2018.1516247
1643. Mission-Phase Feature Learning for eVTOL Li-Ion Battery Prognostics: A Leakage-Safe Cell-Held-Out Benchmark for SOC, SOH, and RUL S. Yan & M. Wiston https://doi.org/10.3390/batteries12090322
1644. Integrating CCME-WQI and Machine Learning for Groundwater Quality in the Sedrata Plain F. Nadour et al. https://doi.org/10.2478/eces-2026-0025
1645. Machine-Learning Proxy of Air-Quality Variability Associated with Intercontinental Bridge Traffic over the Bosphorus in Istanbul E. Birinci et al. https://doi.org/10.3390/atmos17101024
1646. Enhanced adaptive LSTM framework for robust early-life prediction of lithium-ion battery degradation M. Safitri et al. https://doi.org/10.1016/j.rineng.2026.109664
1647. Bayesian spatial Durbin modelling of stunting prevalence across Indonesian districts F. Yanuar et al. https://doi.org/10.4081/gh.2026.1441
1648. A new approach to monitor and assess the damage caused by two-spotted spider mite T. Uygun et al. https://doi.org/10.1007/s10493-020-00561-8
1649. 2D Prediction of the Nutritional Composition of Dishes from Food Images: Deep Learning Algorithm Selection and Data Curation Beyond the Nutrition5k Project R. Bianco et al. https://doi.org/10.3390/nu17132196
1650. Congestion-Aware Traffic Forecasting with Physics-Guided Spatio-Temporal Graph Convolutional Networks Y. Zhang & J. Zhang https://doi.org/10.3390/app16073546
1651. Can the variability in precipitation simulations across GCMs be reduced through sensible bias correction? H. Nguyen et al. https://doi.org/10.1007/s00382-016-3510-z
1652. Studying the Reliability of Estimating Groundwater Remediation Cost Based on Qualitative Time-Series Data for an Aquifer F. Qaderi et al. https://doi.org/10.1007/s40996-023-01158-y
1653. Use of technological resources in the era of artificial intelligence and its effect on academic performance Y. Marín et al. https://doi.org/10.3389/fcomp.2026.1876401
1654. Factores que influyen en el desempeño de estudiantes de Ciencias Económicas en Saber Pro Y. Molina-Hurtado et al. https://doi.org/10.17227/rce.num99-21998
1655. Unveiling the Multi-Dimensional Spatio-Temporal Fusion Transformer (MDSTFT): A Revolutionary Deep Learning Framework for Enhanced Multi-Variate Time Series Forecasting S. Wang et al. https://doi.org/10.1109/ACCESS.2024.3444788
1656. Development and Validation of Data Acquisition System for Real-Time Thermal Environment Monitoring in Animal Facilities C. Oliveira et al. https://doi.org/10.3390/agriengineering7020045
1657. Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin S. Meshram et al. https://doi.org/10.1007/s13201-022-01644-0
1658. Principles of QSAR Modeling P. Gramatica https://doi.org/10.4018/IJQSPR.20200701.oa1
1659. Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression R. Deo et al. https://doi.org/10.1016/j.renene.2022.12.048
1660. Full body musculoskeletal model for simulations of gait in persons with transtibial amputation A. Willson et al. https://doi.org/10.1080/10255842.2022.2065630
1661. Improvements of the operational rating system for existing residential buildings J. Jeong et al. https://doi.org/10.1016/j.apenergy.2017.02.036
1662. Machine learning model to predict rate constants for sonochemical degradation of organic pollutants I. Na et al. https://doi.org/10.1016/j.ultsonch.2024.107032
1663. A hierarchical generative framework for the computational re-animation of Dunhuang dance Q. Zhang et al. https://doi.org/10.1057/s41599-026-07681-3
1664. Voiceless Stop Consonant Modelling and Synthesis Framework Based on MISO Dynamic System G. Korvel & B. Kostek https://doi.org/10.1515/aoa-2017-0039
1665. Hydrological analysis and hydraulic modeling of floods: insights from Oued Lahdar (Upper Inaouène, Morocco) H. Fattasse et al. https://doi.org/10.1007/s42990-026-00238-1
1666. Heavy-Tailed Self-Similarity Modeling for Single Image Super Resolution G. Chantas et al. https://doi.org/10.1109/TIP.2020.3038521
1667. Forecasting UK Electricity and Gas Demand Under RCP Scenarios for Net-Zero Energy Security Using ML D. Razeghi-Jahromi et al. https://doi.org/10.3390/en19163830
1668. Climate change and its impact on rice acreage in high-latitude regions of China: an estimation by machine learning Y. Yu et al. https://doi.org/10.1108/IJCCSM-11-2020-0124
1669. QSAR modeling for predicting reproductive toxicity of chemicals in rats for regulatory purposes N. Basant et al. https://doi.org/10.1039/C6TX00083E
1670. Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not T. Hodson https://doi.org/10.5194/gmd-15-5481-2022
1671. Fast High-Dimensional Parameter Optimization for Turbine Blade Manufacturing Using the Powerball L-BFGS Method Under Incomplete Measurements C. Cheng et al. https://doi.org/10.1109/TIM.2024.3418071
1672. Bangladesh’s Climate-Stressed Agriculture: Sectoral Vulnerabilities Via Machine Learning M. Emam et al. https://doi.org/10.1007/s41748-025-00835-4
1673. Experimental Validation of Upper-Limb Arm Motion Measured by Wearable IMUs Using a Kinect-Based Reference System M. Ceccarelli et al. https://doi.org/10.3390/biomechanics6020058
1674. Machine Learning‐Aided Process Design: Modeling and Prediction of Transformation Temperature for Pearlitic Steel L. Qiao et al. https://doi.org/10.1002/srin.202100267
1675. NO2 mapping of Perth bushfire utilizing Sentinel-5P TROPOMI S. Neyrizi et al. https://doi.org/10.1088/1755-1315/1418/1/012081
1676. Ground Deformation Analysis Using InSAR and Backpropagation Prediction with Influencing Factors in Erhai Region, China Y. Wang et al. https://doi.org/10.3390/su11102853
1677. Generative adversarial approach to urban areas NDVI estimation: A case study of Łódź, Poland M. Adamiak et al. https://doi.org/10.14746/quageo-2023-0007
1678. An automated phenotyping method for Chinese Cymbidium seedlings based on 3D point cloud Y. Zhou et al. https://doi.org/10.1186/s13007-024-01277-1
1679. Unified process model-based assessment of environmental interactions and ecosystem services of a managed fishpond-reed agroecosystem P. Sharma et al. https://doi.org/10.1016/j.ecolmodel.2025.111151
1680. Electrical Resistivity-Based Prediction of Corrosion-Affected Areas in Reinforced Concrete V. Agbayani et al. https://doi.org/10.3390/buildings16040886
1681. A hybrid air quality early-warning framework: An hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms E. Sharma et al. https://doi.org/10.1016/j.scitotenv.2019.135934
1682. Nonparametric versus parametric (both unimodal and mixed) probability distribution in hourly wind speed modelling for some regions of Tamil Nadu state in India N. Natarajan & S. Latif https://doi.org/10.1007/s00477-023-02587-x
1683. TransPark: Leveraging Transfer Learning With Transformers for Intelligent Parking Systems C. Chakraborttii & L. Cheng https://doi.org/10.1109/OJITS.2025.3649601
1684. Damage detection of spent nuclear fuel canisters using frequency response functions M. Aghagholizadeh et al. https://doi.org/10.1016/j.anucene.2023.109707
1685. Disaggregating Population Data and Evaluating the Accuracy of Modeled High-Resolution Population Distribution—The Case Study of Germany S. Eichhorn https://doi.org/10.3390/su12103976
1686. Impact of Hydrometeorological and Climatic Pressures on Greek Rivers: Implementation into the Water Framework Directive 2000/60 A. Mentzafou et al. https://doi.org/10.3390/hydrology13090232
1687. Meteorological Variables Forecasting System Using Machine Learning and Open-Source Software J. Segovia et al. https://doi.org/10.3390/electronics12041007
1688. Data-Driven Insights into Controlling the Reactivity of Supplementary Cementitious Materials in Hydrated Cement A. Degefa et al. https://doi.org/10.1186/s40069-024-00677-w
1689. Artificial Intelligence Approach for Tomato Detection and Mass Estimation in Precision Agriculture J. Lee et al. https://doi.org/10.3390/su12219138
1690. Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and Best Practices for Machine Learning in Chemistry G. Vishwakarma et al. https://doi.org/10.1016/j.trechm.2020.12.004
1691. Semivariogram-based distance function for gradual coverage location models F. Simoyama et al. https://doi.org/10.1016/j.eswa.2024.126167
1692. Data-driven Livestock Manure Allocation: Integrating Soil Analysis and Nutrient Requirements with Machine Learning D. Selçuk & Ü. Kızıl https://doi.org/10.29133/yyutbd.1817079
1693. A review of machine learning and deep learning models, features, and applications for solar PV forecasting D. Sharma et al. https://doi.org/10.1186/s43067-026-00382-6
1694. A Method for Prediction of Waterlogging Economic Losses in a Subway Station Project H. Wu & J. Wang https://doi.org/10.3390/math9121421
1695. Extreme warm and cold waves derived from multiple high-resolution gridded datasets in Egypt H. Aboelkhair & M. Morsy https://doi.org/10.1007/s00704-023-04692-x
1696. Model-based process design for surfactin production with Bacillus subtilis E. Hiller et al. https://doi.org/10.1186/s13568-025-01978-3
1697. Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran M. Ghorbani et al. https://doi.org/10.1007/s00704-017-2244-0
1698. Bottom-Up Load Forecasting With Markov-Based Error Reduction Method for Aggregated Domestic Electric Water Heaters X. Gong et al. https://doi.org/10.1109/TIA.2019.2936330
1699. Air pollution measurement errors: is your data fit for purpose? S. Diez et al. https://doi.org/10.5194/amt-15-4091-2022
1700. Geometrical Analysis of an Oscillating Water Column Converter Device Considering Realistic Irregular Wave Generation with Bathymetry A. Mocellin et al. https://doi.org/10.3390/jeta1010003
1701. Comparison of SES method and SARIMA model in predicting the number of admissions in the department of neurology W. Yang et al. https://doi.org/10.1038/s41598-025-03106-4
1702. Development and validation of the mobile adherence satisfaction scale (MASS) for medication adherence apps R. Rana et al. https://doi.org/10.1016/j.sapharm.2024.07.004
1703. Time Domain Reflectometry flat sensor for non-invasive monitoring of moisture changes in building materials Z. Suchorab et al. https://doi.org/10.1016/j.measurement.2020.108091
1704. Development of a CFD-Suitable Deep Neural Network Model for Laminar Burning Velocity A. Ambrutis & M. Povilaitis https://doi.org/10.3390/app12157460
1705. Deciphering Urban Flood Drivers: An Explainable Machine Learning Approach to Vulnerability Assessment in Indonesian Catchments A. Sodri et al. https://doi.org/10.3390/hydrology13070184
1706. Transient thermal regime trough the constitutive matrix applied to asynchronous electrical machine using the cell method P. González-Domínguez et al. https://doi.org/10.1515/phys-2018-0090
1707. 3-D Dynamic Modeling and Validation of Human Arm for Torque Determination During Eating Activity Using Kane’s Method Z. Hussain & N. Azlan https://doi.org/10.1007/s40997-019-00299-8
1708. Estimating Above-Ground Biomass of Potato Using Random Forest and Optimized Hyperspectral Indices H. Yang et al. https://doi.org/10.3390/rs13122339
1709. Soft Sensor Modeling Method Considering Higher-Order Moments of Prediction Residuals F. Ma et al. https://doi.org/10.3390/pr12040676
1710. Pricing strategy for household energy-saving option (HESO): A novel option-based intervention for promoting household energy efficiency Q. Xu et al. https://doi.org/10.1016/j.eiar.2022.106969
1711. Beyond the ordinary metrics on the evaluation of historical Euro-CORDEX simulations over Türkiye: the mutual information approach S. Vazifehkhah et al. https://doi.org/10.1007/s00704-023-04492-3
1712. A critical review on selecting performance evaluation metrics for supervised machine learning models in wastewater quality prediction H. Khoshvaght et al. https://doi.org/10.1016/j.jece.2025.119675
1713. A database of optimal integration times for Lagrangian studies of atmospheric moisture sources and sinks R. Nieto & L. Gimeno https://doi.org/10.1038/s41597-019-0068-8
1714. West Africa’s CO2 emissions: investigating the economic indicators, forecasting, and proposing pathways to reduce carbon emission levels B. Ameyaw et al. https://doi.org/10.1007/s11356-020-07849-7
1715. Evaluation of Terrestrial and Mobile Scanner Technologies for Part-Built Information Modeling S. Sepasgozar et al. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001574
1716. Daily global solar radiation modeling using data-driven techniques and empirical equations in a semi-arid climate S. Samadianfard et al. https://doi.org/10.1080/19942060.2018.1560364
1717. A deep hashing method of likelihood function adaptive mapping H. Su et al. https://doi.org/10.1007/s00521-022-07962-3
1718. An exploratory in N -doped carbon dots as green fluorescence probes for Hg(II) ions detection A. Roozbahani et al. https://doi.org/10.1080/09593330.2023.2220891
1719. NVNMD-v2: Scalable and Accurate Deep Learning Molecular Dynamics Model Based on Non-Von Neumann Architectures X. Yu et al. https://doi.org/10.1021/acs.jctc.5c01050
1720. Evaluating the Impact of the Spatial Resolution of Digital Elevation Models on Flood Modelling E. Adesina et al. https://doi.org/10.1007/s11269-025-04206-6
1721. An optimized artificial neural network model for the prediction of rate of hazardous chemical and healthcare waste generation at the national level V. Adamović et al. https://doi.org/10.1007/s10163-018-0741-6
1722. Reforming energy prices to achieve sustainable energy consumption in the agriculture sector of Iran’s provinces: Using game approach P. Pakrooh et al. https://doi.org/10.1016/j.jclepro.2021.126146
1723. Exploring soil pollution patterns in Ghana's northeastern mining zone using machine learning models D. Kwayisi et al. https://doi.org/10.1016/j.hazadv.2024.100480
1724. Digital Mapping of Soil Profile Properties using Remote Sensing and Topography Covariates in the Central Dry Zone of Myanmar A. Win et al. https://doi.org/10.1007/s42729-026-03457-5
1725. Spatio-temporal feature fusion for real-time prediction of TBM operating parameters: A deep learning approach X. Fu & L. Zhang https://doi.org/10.1016/j.autcon.2021.103937
1726. TIME SERIES-BASED APPROACHES FOR IMPROVING WIND POWER GENERATION FORECAST ACCURACY Y. Knaytov et al. https://doi.org/10.55452/1998-6688-2023-20-2-103-114
1727. Distribution of CO2 Concentration and Its Spatial Influencing Indices in Urban Park Green Space Y. Jiang et al. https://doi.org/10.3390/f14071396
1728. A Data-Driven Approach to Estimating Passenger Boarding in Bus Networks G. Bongiovi et al. https://doi.org/10.3390/app16031384
1729. Impact of Atmospheric Correction Methods Parametrization on Soil Organic Carbon Estimation Based on Hyperion Hyperspectral Data P. Mruthyunjaya et al. https://doi.org/10.3390/rs14205117
1730. Predicting and optimizing the mechanical properties of rejuvenated asphalt mix with RAP content M. Islam et al. https://doi.org/10.1007/s00521-024-10553-z
1731. Hybrid agent-based modeling of rooftop solar photovoltaic adoption by integrating the geographic information system and data mining technique M. Lee & T. Hong https://doi.org/10.1016/j.enconman.2018.12.096
1732. Federated Learning for Decentralized Electricity Market Optimization: A Review and Research Agenda T. Miller et al. https://doi.org/10.3390/en18174682
1733. Toward a Unified Performance Metric for Benchmarking Steganography Systems T. Rabie et al. https://doi.org/10.1142/S0218126620500425
1734. The 2016 US Presidential Elections: What Went Wrong in Pre-Election Polls? Demographics Help to Explain R. Zeedan https://doi.org/10.3390/j2010007
1735. Machine learning: Modeling increment in diameter of individual trees on Atlantic Forest fragments I. Tavares Júnior et al. https://doi.org/10.1016/j.ecolind.2020.106685
1736. Co-gasification of biomass and plastic waste for green and blue hydrogen Production: Novel process development, economic, exergy, advanced exergy, and exergoeconomics analysis Y. Ayub et al. https://doi.org/10.1016/j.cej.2023.148080
1737. Kinematic analysis of continuum robots based on vector form intrinsic finite element method J. Li et al. https://doi.org/10.1177/09544062261432255
1738. Multivariate modeling of pan evaporation in monthly temporal resolution using a hybrid evolutionary data-driven method (case study: Urmia Lake and Gavkhouni basins) A. Emadi et al. https://doi.org/10.1007/s10661-021-09060-8
1739. A Comparison on LSTM Deep Learning Method and Random Walk Model Used on Financial and Medical Applications: An Example in COVID-19 Development Prediction Y. Yao et al. https://doi.org/10.1155/2022/4383245
1740. Modeling of CCT diagrams for tool steels using different machine learning techniques X. Geng et al. https://doi.org/10.1016/j.commatsci.2019.109235
1741. Effects of Estuarine Environmental Heterogeneity on the Habitat of Gobiidea Species Larvae L. Zhai et al. https://doi.org/10.1002/mcf2.10241
1742. Improving the resolution of solar energy potential maps derived from global DSMs for rooftop solar panel placement using deep learning M. Hosseini & H. Bagheri https://doi.org/10.1016/j.heliyon.2024.e41193
1743. Development of a Neuro-Fuzzy System for Assessing Information Management on the Shop Floor E. Drigo et al. https://doi.org/10.1109/ACCESS.2020.3038061
1744. Multivariate optimization and computational insights for the effective decolorization of reactive orange 107 using Rhizoclonium hieroglyphicum and its sustainable reuse potential A. Swathilakshmi et al. https://doi.org/10.1080/15226514.2025.2579144
1745. Prediction of sardine and anchovy catches by double-boat purse seiners in the northern Persian Gulf using machine learning models E. Soleimani et al. https://doi.org/10.1016/j.dsr2.2025.105502
1746. Data-Driven Prediction of Crystal Size Metrics Using LSTM Networks and In Situ Microscopy in Seeded Cooling Crystallization I. Vrban et al. https://doi.org/10.3390/pr13061860
1747. Epidemiological Investigation Model of Novel Coronavirus Pneumonia Based on Data Mining Technology K. Chen et al. https://doi.org/10.1051/e3sconf/202129203026
1748. A Novel LUTI Model Calibration Using Differential Evolution Algorithm A. Skandary et al. https://doi.org/10.1109/ACCESS.2021.3135949
1749. Predicting 28-Day Cement Compressive Strength for Delayed Quality Control Using Early-Age Strength and a Weighted CatBoost–XGBoost Ensemble M. Topaloğlu et al. https://doi.org/10.3390/app16147017
1750. A construction cost estimation framework using DNN and validation unit S. Saeidlou & N. Ghadiminia https://doi.org/10.1080/09613218.2023.2196388
1751. Research on neural network prediction method for electrolyte concentration based on RF coaxial probes J. Qian et al. https://doi.org/10.1063/5.0288061
1752. View Factors Approach for Bifacial Photovoltaic Array Modeling: Bifacial Gain Sensitivity Analysis R. Benbba et al. https://doi.org/10.1115/1.4066500
1753. A survey of uncover misleading and cyberbullying on social media for public health O. Darwish et al. https://doi.org/10.1007/s10586-022-03706-z
1754. The Comparison of Long Short-Term Memory Neural Network and Deep Forest for the Evaporation Duct Height Prediction Q. Liao et al. https://doi.org/10.1109/TAP.2023.3254201
1755. Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models M. Bayatvarkeshi et al. https://doi.org/10.1016/j.compag.2021.106158
1756. Forecasting the InSAR-monitored 3D displacements for urban buildings using attention-enhanced LSTM Y. Du et al. https://doi.org/10.1007/s13349-025-01012-x
1757. Design and development of a model for accuracy assessment and measurement error quantification of optical rotary encoders under vibration V. Krcheva et al. https://doi.org/10.5937/fme2504545K
1758. Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method J. Hwang et al. https://doi.org/10.3349/ymj.2022.63.7.683
1759. Numerical Study on the performance of a heat pump-driven-DCMD for sustainable desalination S. Oh et al. https://doi.org/10.3389/fenrg.2022.1053219
1760. Estimation of live bodyweight from linear body measurements and body condition score in the West African Savannah Shorthorn cattle in North-West Benin S. Vanvanhossou et al. https://doi.org/10.1080/23311932.2018.1549767
1761. Correcting Hardening Artifacts of Aero-Engine Blades with an Iterative Linear Fitting Technique Framework Y. Gao et al. https://doi.org/10.3390/s24062001
1762. Downscaling of soil moisture in the Wujiang River Basin based on integrated decision tree-based machine learning P. Qu et al. https://doi.org/10.1080/22797254.2026.2641527
1763. Pose-aware monocular localization of occluded pedestrians in 3D scene space M. Rahimi et al. https://doi.org/10.1016/j.ophoto.2021.100006
1764. Rapid elemental prediction of heterogeneous tropical soils from pXRF data: a comparison of models via linear regressions and machine learning algorithms Á. Faria et al. https://doi.org/10.1071/SR22168
1765. QSAR modeling of algal low level toxicity values of different phenol and aniline derivatives using 2D descriptors A. Seth & K. Roy https://doi.org/10.1016/j.aquatox.2020.105627
1766. An introduction to machine learning and analysis of its use in rheumatic diseases K. Kingsmore et al. https://doi.org/10.1038/s41584-021-00708-w
1767. Degraded coastal agricultural lands hold significant soil carbon stocks and are potential candidates for blue carbon restoration I. Cooray et al. https://doi.org/10.1016/j.envres.2026.123742
1768. Nonlinear modeling of industrial boiler NOx emissions G. Ronquillo-Lomeli et al. https://doi.org/10.1080/10962247.2021.1980451
1769. A self-conformation-aware pre-training framework for molecular property prediction with substructure interpretability J. Qiao et al. https://doi.org/10.1038/s41467-025-59634-0
1770. A new approach to detect mildew disease on cucumber (Pseudoperonospora cubensis) leaves with image processing M. Ozguven & Z. Altas https://doi.org/10.1007/s42161-022-01178-z
1771. Salient Object Detection by Spatiotemporal and Semantic Features in Real-Time Video Processing Systems Y. Fang et al. https://doi.org/10.1109/TIE.2019.2956418
1772. Estimation of Cerebral Blood Flow and Arterial Transit Time From Multi‐Delay Arterial Spin Labeling MRI Using a Simulation‐Based Supervised Deep Neural Network S. Ishida et al. https://doi.org/10.1002/jmri.28433
1773. Generation of rainfall scenarios based on rainfall transition probability to determine temporal distribution of independent rainstorms H. Cha et al. https://doi.org/10.1007/s00477-024-02844-7
1774. Extreme Learning Machine Model for State-of-Charge Estimation of Lithium-Ion Battery Using Gravitational Search Algorithm M. Hossain Lipu et al. https://doi.org/10.1109/TIA.2019.2902532
1775. CFD modelling of an urban microclimate during a heat wave: Coupling solar radiation and heat transfer D. Nascimento et al. https://doi.org/10.1016/j.uclim.2025.102486
1776. Effects of various input levels and different soil water retention curve models on water content estimation using different statistical methods H. Bayat & E. Ebrahimi https://doi.org/10.2166/nh.2015.219
1777. Prediction of sulphur dioxide (SO2) in air by using bagging, ANN and M5P: a case study, Gaya and Tirupati, India S. Devi et al. https://doi.org/10.1007/s12517-022-09725-9
1778. Drone‐Based Prediction of the Planetary Boundary Layer Height Using Artificial Intelligence With Scarce Data: A Case Study in Quito, Ecuador L. Muñoz et al. https://doi.org/10.1155/adme/6836397
1779. Geological seabed stability model for informing Irish offshore renewable energy opportunities J. Peters et al. https://doi.org/10.5194/adgeo-54-55-2020
1780. Enhancing perovskite solar cell efficiency and stability: a multimodal prediction approach integrating microstructure, composition, and processing technology W. Rahman et al. https://doi.org/10.1039/D5NR00364D
1781. A new approach for processing climate missing databases applied to daily rainfall data in Soummam watershed, Algeria A. Aieb et al. https://doi.org/10.1016/j.heliyon.2019.e01247
1782. Predictive Modeling for Pandemic Forecasting: A COVID-19 Study in New Zealand and Partner Countries O. Baker et al. https://doi.org/10.3390/ijerph22040562
1783. Heartbeat sound classification using a hybrid adaptive neuro-fuzzy inferences system (ANFIS) and artificial bee colony P. Keikhosrokiani et al. https://doi.org/10.1177/20552076221150741
1784. Adaptive Neuro‐Fuzzy Inference System integrated with solar zenith angle for forecasting sub‐tropical Photosynthetically Active Radiation R. Deo et al. https://doi.org/10.1002/fes3.151
1785. AlphaZeroBlock: A deep reinforcement learning and Monte Carlo tree search approach for intelligent 3D track block assembly Z. Liu et al. https://doi.org/10.1016/j.eswa.2026.132439
1786. Propulsion and photovoltaic charging system parameter computation for an all-electric boat O. Yüksel et al. https://doi.org/10.1080/17445302.2023.2195239
1787. Decision-making in a fast fashion company in the Industry 4.0 era: a Digital Twin proposal to support operational planning C. dos Santos et al. https://doi.org/10.1007/s00170-021-07543-z
1788. Sensor-Based Yield Prediction in Durum Wheat Under Semi-Arid Conditions Using Machine Learning Across Zadoks Growth Stages S. Rufaioğlu et al. https://doi.org/10.3390/rs17142416
1789. Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India A. Arora et al. https://doi.org/10.1016/j.scitotenv.2020.141565
1790. Prediction of buckling damage of steel equal angle structural members using hybrid machine learning techniques N. Ho et al. https://doi.org/10.1038/s41598-025-87869-w
1791. Cross-sectoral assessment of the performance gap using calibrated building energy performance simulation N. Jain et al. https://doi.org/10.1016/j.enbuild.2020.110271
1792. An Automatic Denoising Method for NMR Spectroscopy Based on Low-Rank Hankel Model T. Qiu et al. https://doi.org/10.1109/TIM.2021.3109743
1793. Utilizing Artificial Intelligence Approaches to Determine the Shear Strength of Steel Beams with Flat Webs A. Elamary et al. https://doi.org/10.3390/met13020232
1794. No-reference quality assessment for image-based assessment of economically important tropical woods H. Rajagopal et al. https://doi.org/10.1371/journal.pone.0233320
1795. Agricultural planning grounded in regional rainfall patterns in the Colombian Orinoquia: An essential step for advancing climate-adapted and sustainable agriculture C. Ocampo-Marulanda et al. https://doi.org/10.1515/opag-2025-0465
1796. Efficient structural analysis of gas turbine blades T. Rogge et al. https://doi.org/10.1108/AEAT-05-2016-0085
1797. Experimental evaluation of the saturation-tone method for C-band EDFA gain characterization A. Aygar & F. Durak https://doi.org/10.1364/AO.612731
1798. An efficient approach based on radial basis functions for solving stochastic fractional differential equations N. Ahmadi et al. https://doi.org/10.1007/s40096-017-0211-7
1799. Laboratory evaluation of ERT for seepage localization in earthen dams: Positional accuracy for dam health monitoring N. Babazadeh Abrbekouh & R. Ghiassi https://doi.org/10.1177/14759217261422380
1800. Machine Learning-Enhanced Laser-Induced Breakdown Spectroscopy for Quantitative Analysis of High-Concentration Uranium in Molten Salt B. Liang et al. https://doi.org/10.1007/s41664-026-00470-6
1801. Hybrid machine learning models for predicting Marshall stability and flow in asphalt mixtures with optimal feature selection H. Gundogdu et al. https://doi.org/10.1007/s11831-026-10751-z
1802. Privacy-preserving and sparsity-aware location-based prediction method for collaborative recommender systems S. Meng et al. https://doi.org/10.1016/j.future.2019.02.016
1803. Whole-process performance prediction and optimization of CIGS solar cells via interpretable machine learning J. Cui et al. https://doi.org/10.1016/j.jechem.2026.03.052
1804. Bridging Extreme Data Gaps: SAR–Optical Fusion Guided by Dual-Temporal SAR Differences Z. Ge et al. https://doi.org/10.1109/JSTARS.2026.3696803
1805. Machine learning-enhanced breakthrough modeling of malachite green adsorption onto superparamagnetic activated carbon S. Sudarsan et al. https://doi.org/10.1016/j.ceja.2025.100932
1806. Integrating Multitemporal SAR and Optical Information for Missing Optical Imagery Generation C. Dong et al. https://doi.org/10.1109/TGRS.2024.3451558
1807. Accurate and efficient stock market index prediction: an integrated approach based on VMD-SNNs X. Chen et al. https://doi.org/10.1080/02664763.2024.2395961
1808. Design and Validation of an Active Headrest System with Integrated Sensing in Rear-End Crash Scenarios A. Radu et al. https://doi.org/10.3390/s25144291
1809. Artificial neural networks to correlate structure and CO2 separation performance of mixed matrix membranes containing 2D fillers M. Shariatifar et al. https://doi.org/10.1016/j.advmem.2025.100171
1810. Investigation and evaluation of algorithms for unmanned aerial vehicle multispectral image registration L. Meng et al. https://doi.org/10.1016/j.jag.2021.102403
1811. Measuring inter-individual differences in behavioural types of gilthead seabreams in the laboratory using deep learning M. Signaroli et al. https://doi.org/10.7717/peerj.13396
1812. Hybrid process-based and deep learning for river nutrient prediction under limited monitoring data J. Tang et al. https://doi.org/10.1016/j.jhydrol.2026.135098
1813. Deep Learning-Based Performance Modeling of Hydrogen Fuel Cells Using Artificial Neural Networks: A Comparative Study of Optimizers H. Abbade et al. https://doi.org/10.3390/pr13051453
1814. Hybrid forecasting of university electricity demand using time series and deep learning M. Baek & Y. Seo https://doi.org/10.1016/j.enbuild.2025.116400
1815. Early detection of West Nile virus in France: quantitative assessment of syndromic surveillance system using nervous signs in horses C. FAVERJON et al. https://doi.org/10.1017/S0950268816002946
1816. Using machine learning techniques to reconstruct the signal observed by the GRACE mission based on AMSR-E microwave data V. Szabó et al. https://doi.org/10.2478/mgrsd-2023-0033
1817. Comparative study of machine learning techniques to predict fuel consumption of a marine diesel engine O. Yuksel et al. https://doi.org/10.1016/j.oceaneng.2023.115505
1818. Development and validation of regional weighted mean temperature models for tropical Africa using radiosonde data R. Ssenyunzi & G. Andima https://doi.org/10.1016/j.jastp.2026.106924
1819. Dynamic model to describe kinetic behavior of Listeria monocytogenes in smoked salmon J. Kang et al. https://doi.org/10.1111/jfs.12925
1820. Verification of deterministic solar forecasts D. Yang et al. https://doi.org/10.1016/j.solener.2020.04.019
1821. Forecast Errors Attributed to Synoptic Features Q. Yu et al. https://doi.org/10.1002/met.70093
1822. Comprehensive quality assessment of satellite- and model-based soil moisture products against the COSMOS network in Germany T. Schmidt et al. https://doi.org/10.1016/j.rse.2023.113930
1823. Improving the accuracy of decoding monkey brain–machine interface data by estimating the state of unobserved cell assemblies T. Asahina et al. https://doi.org/10.1016/j.jneumeth.2022.109764
1824. Removal of a quaternary ammonium compound by electrocoagulation: Mechanistic analysis and multi-response optimization using response surface methodology and machine learning A. Tavakoli et al. https://doi.org/10.1016/j.watres.2025.124935
1825. From Informality to Green Development: How the Shadow Economy Affects Green Finance, Green Innovation, and Green Trade S. Rahman et al. https://doi.org/10.1002/bse.71038
1826. Robust Estimation-Based Control Strategies for Induction Motors F. Stîngă et al. https://doi.org/10.1155/2020/9235701
1827. UStyle: Waterbody Style Transfer of Underwater Scenes by Depth-Guided Feature Synthesis M. Siddique et al. https://doi.org/10.1109/JOE.2025.3647814
1828. Monitoring Coastal Chlorophyll-a Concentrations in Coastal Areas Using Machine Learning Models Y. Kwon et al. https://doi.org/10.3390/w10081020
1829. Machine Learning‐Enhanced Prediction of Inorganic Semiconductor Bandgaps for Advancing Optoelectronic Technologies M. Zeb et al. https://doi.org/10.1002/adts.202400190
1830. Meteorological Modeling Using the WRF-ARW Model for Grand Bay Intensive Studies of Atmospheric Mercury F. Ngan et al. https://doi.org/10.3390/atmos6030209
1831. Development and evaluation of FLFAcs – A new Flood Loss Function for Australian commercial structures R. Hasanzadeh Nafari et al. https://doi.org/10.1016/j.ijdrr.2016.03.007
1832. Real-world validated MVEM-based modeling and SoC-dependent driving scenario definition for a parallel hybrid vehicle E. Savran https://doi.org/10.1177/09544070261454760
1833. Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling H. Beck et al. https://doi.org/10.5194/hess-21-6201-2017
1834. Machine learning-optimized microwave pyrolysis of sludge: Optimal conditions and mechanism analysis for synergistic purification of multi-component harmful gases X. Song et al. https://doi.org/10.1016/j.ijhydene.2026.154518
1835. Simultaneous prediction of multiple soil components using Mid-Infrared Spectroscopy and the GADF-Swin Transformer model W. Guo et al. https://doi.org/10.1016/j.compag.2025.110507
1836. Comparative data-driven prediction of thermal performance of cylindrical lithium-ion battery packs M. Ozturk Kirkar https://doi.org/10.1016/j.applthermaleng.2026.131677
1837. Probabilistic analysis of stress effects on an unsaturated soil slope stability using convolutional neural networks and Bayesian optimisation C. Qu et al. https://doi.org/10.1016/j.enggeo.2025.108511
1838. A comparative study of hybrid artificial neural network models for predicting Cr(VI) adsorption onto activated carbon C. Sutherland et al. https://doi.org/10.5004/dwt.2018.21930
1839. Hindcasting of tropical cyclone winds and waves S. Zieger et al. https://doi.org/10.1007/s10236-021-01443-2
1840. Revisiting the Impact of Dependency Network Metrics on Software Defect Prediction L. Gong et al. https://doi.org/10.1109/TSE.2021.3131950
1841. Contribution to advancing aquifer geometric mapping using machine learning and deep learning techniques: a case study of the AL Haouz-Mejjate aquifer, Marrakech, Morocco L. El Mezouary et al. https://doi.org/10.1007/s13201-024-02162-x
1842. Optimising and analysis of the hydraulic performance of a water dispersion needle sprinkler using RF-NSGA II and CFD H. Li et al. https://doi.org/10.1016/j.biosystemseng.2025.02.009
1843. Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia M. Al-Musaylh et al. https://doi.org/10.1016/j.aei.2017.11.002
1844. Spatiotemporal Geostatistical Analysis and Global Mapping of CH4 Columns from GOSAT Observations L. Li et al. https://doi.org/10.3390/rs14030654
1845. Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data T. Mari et al. https://doi.org/10.1016/j.jpain.2021.07.011
1846. Wireless signal enhancement based on generative adversarial networks X. Zhou et al. https://doi.org/10.1016/j.adhoc.2020.102151
1847. A Clinically Informed ML-IEMS Architecture for Wearable Vital-sign Monitoring with Retrospective Simulation K. El Amri et al. https://doi.org/10.1007/s42979-026-05326-5
1848. Sentinel-2 time series reveal species-specific responses in temperate conifer dieback H. Carletti et al. https://doi.org/10.1080/22797254.2025.2547386
1849. A composition-based predictive model for the transformation strain of NiTi shape memory alloys S. Zadeh et al. https://doi.org/10.1016/j.actamat.2025.120861
1850. Analysis of the temporal evolution of the spectral and spatial sensitivities of a support vector regression maize yield algorithm N. Burglewski et al. https://doi.org/10.1016/j.compag.2025.110930
1851. New machine learning model based on the time factor for e-commerce recommendation systems D. Tran & J. Huh https://doi.org/10.1007/s11227-022-04909-2
1852. Ethanol production from different medium compositions of rice husk hydrolysate by using Scheffersomyces stipitis in a repeated-batch biofilm reactor and its modeling N. Bader et al. https://doi.org/10.1016/j.procbio.2020.09.018
1853. Hybrid random forest-based models for predicting shear strength of structural surfaces based on surface morphology parameters and metaheuristic algorithms J. Zhou et al. https://doi.org/10.1016/j.conbuildmat.2023.133911
1854. Application of remote sensing and machine learning in mangrove above ground biomass estimation H. Etemadi et al. https://doi.org/10.1007/s12665-026-13016-x
1855. Prediction of Air Quality Index (AQI) using machine learning-based tree models—a case study of Gurugram City, India A. Kumar et al. https://doi.org/10.1007/s00704-025-05535-7
1856. Hyperspectral Estimation of Layer-Specific Leaf Nitrogen Content in Potato Canopy by Integrating Fractional-Order Derivatives and Three-Band Spectral Indices M. Jin et al. https://doi.org/10.3390/plants15132045
1857. Error Characteristics of GNSS Derived TEC G. Ma et al. https://doi.org/10.3390/atmos13020237
1858. How big is the potato (Solanum tuberosum L.) yield gap in Sub-Saharan Africa and why? A participatory approach D. Harahagazwe et al. https://doi.org/10.1515/opag-2018-0019
1859. Evaluation of Compressive Strength of Expanded Polystyrene Concrete Based on Broad Learning System Z. Zhou et al. https://doi.org/10.3390/buildings16040795
1860. Trend-weighted multi-resolution transformer for multi-parametric glucose prediction Ö. Koca & V. Kılıç https://doi.org/10.1016/j.bspc.2025.108885
1861. Biological activities of Lippia gracilis Schauer essential oil and modelling of its effects on bacterial growth W. Oliveira et al. https://doi.org/10.1016/j.micpath.2026.108436
1862. Drivers of Live Cattle Price in the Livestock Trading System of Central Cameroon P. Motta et al. https://doi.org/10.3389/fvets.2017.00244
1863. Groundwater quality in the lower Coata River basin, Lake Titicaca watershed: Potential ecological and human health risks of potentially toxic elements R. Flores-Marquez et al. https://doi.org/10.1016/j.gsd.2026.101692
1864. Development and Evaluation of a Urinary Na/K Ratio Prediction Model: A Systematic Comparison from Attention-Based Deep Learning to Classical Ensemble Approaches E. Yuda et al. https://doi.org/10.3390/bioengineering13020252
1865. Integration of PINN with Conventional Well Logging for Few-Shot TOC Prediction in Ultradeep Source Rocks T. He et al. https://doi.org/10.1021/acsomega.5c10927
1866. Uncertainty of Coupled Model Intercomparison Projects 6 (CMIP6) in Indonesia’s maritime continental region for the historical period H. Agiel et al. https://doi.org/10.1088/1755-1315/1314/1/012020
1867. Short-term electrical load forecasting based on multi-granularity time augmented learning J. Chu et al. https://doi.org/10.1007/s00202-024-02698-w
1868. Enhancing wind power forecasting accuracy under extreme weather: Leveraging a dual-model approach with condition-based classification W. Yuan et al. https://doi.org/10.1016/j.engappai.2025.112656
1869. Effects of waveform design on heat transfer, thermal confinement, and tissue damage in laser interstitial thermal therapy (LITT) for breast tumors P. Sermlao et al. https://doi.org/10.1016/j.rineng.2026.110952
1870. Tactile Elastography Y. Xiang et al. https://doi.org/10.1109/TRO.2025.3577024
1871. Predictive Modeling to Mitigate Greenhouse Gas Emissions in Taiwan’s Diversified Energy Landscape S. Liong et al. https://doi.org/10.1007/s10666-025-10075-5
1872. Cumulative offset analysis of the Central-Southern Yangsan Fault based on topography of Quaternary fluvial terrace N. Kim et al. https://doi.org/10.14770/jgsk.2020.56.2.135
1873. Application of Multivariate Adaptive Regression Splines (MARS) approach in prediction of compressive strength of eco-friendly concrete A. Naser et al. https://doi.org/10.1016/j.cscm.2022.e01262
1874. AQI time series prediction based on a hybrid data decomposition and echo state networks H. Liu & X. Zhang https://doi.org/10.1007/s11356-021-14186-w
1875. Statistical Optimization of Alkaline-Activated Carbonation of Coal Fly Ash for CO2 Sequestration and Heavy Metal Stabilization P. Triwigati et al. https://doi.org/10.1021/acssusresmgt.5c00284
1876. A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate‐Land Surface Variations T. Lan et al. https://doi.org/10.1029/2018WR023160
1877. A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting G. Varone et al. https://doi.org/10.3390/e25020253
1878. Physics-Based Machine Learning for Vibration Mitigation by Open Buried Trenches L. Pereira et al. https://doi.org/10.3390/app152111609
1879. Sea-land breeze diurnal component and its interaction with a cold front on the coast of Sisal, Yucatan: A case study M. Allende-Arandía et al. https://doi.org/10.1016/j.atmosres.2020.105051
1880. Predictive in silico models for aquatic toxicity of cosmetic and personal care additive mixtures Y. Yang & H. Ni https://doi.org/10.1016/j.watres.2023.119981
1881. Normality Test for Influence Function of Mining Surface Subsidence Based on Network Observation Station P. Li et al. https://doi.org/10.1155/2022/2201996
1882. Apple Leave Disease Detection Using Collaborative ML/DL and Artificial Intelligence Methods: Scientometric Analysis A. Bonkra et al. https://doi.org/10.3390/ijerph20043222
1883. Bayesian Networks and GIS-based analysis for flood risk assessment in agriculture during heavy rainfall events P. Gräfe et al. https://doi.org/10.64866/j.ijdscr.2025.10002
1884. High-Resolution Downscaling of GRACE-Derived Groundwater Storage Anomalies using Stacking Ensemble Machine Learning in the Data-Scarce Tropical Catchments S. Karunarathna et al. https://doi.org/10.1007/s41748-026-01022-9
1885. Retweet: A popular information diffusion mechanism – A survey paper S. Firdaus et al. https://doi.org/10.1016/j.osnem.2018.04.001
1886. Parametric study on global estimation models for compressive strength adopting various machine learning algorithms in concrete W. Mesfin & H. Kim https://doi.org/10.1016/j.engappai.2024.108888
1887. Revisiting the future changes in precipitation extremes over the Eastern Tibetan Plateau: from the thermodynamic–dynamic processes to model uncertainty K. Wang et al. https://doi.org/10.1007/s00382-025-07620-z
1888. Transformer-based model for predicting length of stay in intensive care unit in sepsis patients J. Kim et al. https://doi.org/10.3389/fmed.2024.1473533
1889. Unveiling mortality dynamics: a novel mathematical framework across adulthood and aging B. Çığşar & D. Ünal https://doi.org/10.1007/s00180-025-01693-4
1890. VALIDATION OF TROPICAL RAINFALL MEASURING MISSION (TRMM) DATA IN THE UPPER KAPUAS RIVER BASIN S. Barlian Soeryamassoeka et al. https://doi.org/10.33736/jcest.2618.2020
1891. Application of a Generic Participatory Decision Support System for Irrigation Management for the Case of a Wine Grapevine at Epirus, Northwest Greece I. Tsirogiannis et al. https://doi.org/10.3390/horticulturae9020267
1892. Study of underwater sound effects relation to current velocity and Siganus sp. population in seaweed cultivation area M. Kasim et al. https://doi.org/10.1088/1755-1315/1273/1/012014
1893. Intelligent forecasting of tunnel deformation in underground coal mines using a dynamic swarm-tuned adaptive neuro-fuzzy inference system for knowledge-driven ground control S. Mahdevari https://doi.org/10.1016/j.aei.2025.104287
1894. IoT-integrated deep learning for forecasting and decision support in reservoir water management under drought conditions R. Parada & A. Sanz https://doi.org/10.1016/j.iot.2025.101780
1895. Spatio–temporal variation of vegetation heterogeneity in groundwater dependent ecosystems within arid environments K. Mpakairi et al. https://doi.org/10.1016/j.ecoinf.2022.101667
1896. Forecasting Maximum Temperature Trends with SARIMAX: A Case Study from Ahmedabad, India V. Shah et al. https://doi.org/10.3390/su16167183
1897. Accelerated stability transformation method for chaos control of discrete dynamical systems D. Yang et al. https://doi.org/10.1007/s11071-018-4418-4
1898. A Deep Learning Approach to Identify Potential Sites for Pocket Park Installation in Nanjing, China C. Zhou et al. https://doi.org/10.1080/10630732.2024.2402676
1899. Bitcoin Return Volatility Forecasting: A Comparative Study between GARCH and RNN Z. Shen et al. https://doi.org/10.3390/jrfm14070337
1900. Assessing the Impact of Stochastic Perturbations in Cloud Microphysics using GOES-16 Infrared Brightness Temperatures S. Griffin et al. https://doi.org/10.1175/MWR-D-20-0078.1
1901. In silico local QSAR modeling of bioconcentration factor of organophosphate pesticides P. Banjare et al. https://doi.org/10.1007/s40203-021-00087-w
1902. Model order reduction by radial basis function network for sparse reconstruction of an industrial natural gas boiler J. Park et al. https://doi.org/10.1016/j.csite.2022.102288
1903. High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion X. Zhao et al. https://doi.org/10.3390/land13122173
1904. Mapping Aboveground Biomass of Four Typical Vegetation Types in the Poyang Lake Wetlands Based on Random Forest Modelling and Landsat Images R. Wan et al. https://doi.org/10.3389/fpls.2019.01281
1905. Evaluating statistical downscaling methods for future temperature and precipitation projections in the Qilian mountains G. Liu et al. https://doi.org/10.3389/frsen.2026.1890112
1906. Reconstructing Cognitive Sovereignty in the Era of Generative AI: A Mixed-Methods Study on User Correction of AI-Generated Misinformation C. Gu et al. https://doi.org/10.1080/10447318.2025.2601278
1907. Local climate change indications: Historical trends, multi-model projections and implications in Bilate Catchment, Southern Ethiopia H. Gisha Kuma et al. https://doi.org/10.1088/1755-1315/1016/1/012030
1908. Modelling actual evapotranspiration using a two source energy balance model with Sentinel imagery in herbaceous-free and herbaceous-cover Mediterranean olive orchards S. Aguirre-García et al. https://doi.org/10.1016/j.agrformet.2021.108692
1909. Multi-strategy alpha evolution optimization for constrained parameter estimation in Proton Exchange Membrane Fuel Cells S. Aydemir et al. https://doi.org/10.1016/j.enconman.2025.119917
1910. Sediment transport modeling of trenching activities: a case study for the Safaniya coastal waters in the Arabian Gulf A. Saleem et al. https://doi.org/10.1007/s10236-025-01754-8
1911. CTRL: Cross-Modal Transformer With Reinforcement Learning for Climate Causal Discovery J. Liu et al. https://doi.org/10.1109/TAI.2026.3688211
1912. A GRNN-Based Model for ERA5 PWV Adjustment with GNSS Observations Considering Seasonal and Geographic Variations H. Pang et al. https://doi.org/10.3390/rs16132424
1913. Improved sensitivity equation of mode shapes and adaptive strategy with elastic net regularization for structural damage detection Z. Luo et al. https://doi.org/10.1016/j.istruc.2025.109304
1914. Reanalysis of ERA5-land precipitation, PET, SPI and potential water deficit: A detailed examination of Indian monsoon changes by relating hydro climatic stress in Karnataka N. Harishnaika et al. https://doi.org/10.1016/j.pce.2026.104615
1915. Access Point Selection and Localization for Cluster‐Based Realization of a Device‐to‐Device Cell‐Free 6G Communications Network I. Ioannou et al. https://doi.org/10.1049/cmu2.70096
1916. V TİPİ HAVALI BİR GÜNEŞ KOLEKTÖRÜNÜN ISIL PERFORMANSININ DENEYSEL OLARAK İNCELENMESİ VE YAPAY SİNİR AĞLARI İLE MODELLENMESİ D. SAYDAM et al. https://doi.org/10.21923/jesd.935201
1917. Design and combinatorial library generation of azole derivatives as anticancer agents: QSAR, molecular docking and dynamic approach A. Murmu et al. https://doi.org/10.1016/j.lddd.2025.100267
1918. Ecoprovince-specific height-DBH modeling and height comparison of larix kaempferi in South Korea S. Lee et al. https://doi.org/10.1080/13416979.2026.2615480
1919. Edge-Based Short-Term Energy Demand Prediction A. Lekidis & E. Papageorgiou https://doi.org/10.3390/en16145435
1920. Simulation of the hydraulic performance of highway filter drains through laboratory models and stormwater management tools L. Sañudo-Fontaneda et al. https://doi.org/10.1007/s11356-017-9170-7
1921. Prediction of three-dimensional ocean temperature, salinity and current fields based on fourier neural operators G. Xu et al. https://doi.org/10.1016/j.ocemod.2025.102674
1922. Discrepancy in growth resilience to drought among different stand-aged forests declines going from a semi-humid region to an arid region B. Wang et al. https://doi.org/10.1016/j.foreco.2022.120135
1923. Spatial mapping of rice leaf area index using UAV-borne RGB and multispectral data: a comparison of Beer-Lambert law and machine learning algorithms S. Vishwakarma et al. https://doi.org/10.1007/s40808-026-02820-w
1924. Forecasting Brazil’s Energy Matrix Evolution: A Multi-Method Approach to Evaluate Alignment with SDG 7.2 H. Pimentel Tavares & E. da Silva Christo https://doi.org/10.5772/geet.20250064
1925. Future climate projections for South Aegean and Salzburg region based on statistical and dynamical downscaling - similarities and discrepancies M. Bügelmayer-Blaschek et al. https://doi.org/10.1088/2515-7620/addc3f
1926. Time Series Analysis and Forecasting of Solar Generation in Spain Using eXtreme Gradient Boosting: A Machine Learning Approach C. Saigustia & P. Pijarski https://doi.org/10.3390/en16227618
1927. Framework for modeling multi-sector business closure length in earthquake-struck regions Q. Mao et al. https://doi.org/10.1016/j.ijdrr.2020.101916
1928. An innovative integration of torrefaction, gasification, and solid oxide fuel cell for carbon–neutral utilization of biomass waste: Process development, economic, exergy, advanced exergy, and exergoeconomics analysis Y. Ayub et al. https://doi.org/10.1016/j.enconman.2023.117426
1929. Importance of Electrode Selection and Number in Reconstructing Standard Twelve Lead Electrocardiograms A. Butchy et al. https://doi.org/10.3390/biomedicines11061526
1930. Machine learning as a tool for predicting and engineering the next generation of piezoelectric materials R. Guest & S. Guerin https://doi.org/10.1016/j.xcrp.2026.103522
1931. Prediction of CO2 emission from arid soil after addition of exogenous organic matter R. Chaker et al. https://doi.org/10.1016/j.jaridenv.2022.104920
1932. Author profiling using a graph enrichment approach E. Castillo et al. https://doi.org/10.3233/JIFS-169485
1933. Estimating biomass of savanna grasslands as a proxy of carbon stock using multispectral remote sensing L. Chapungu et al. https://doi.org/10.1016/j.rsase.2019.100275
1934. Validation of near infrared spectroscopy as an age-prediction method for plastics A. Alassali et al. https://doi.org/10.1016/j.resconrec.2019.104555
1935. Multi-models machine learning methods for traffic flow estimation from Floating Car Data J. Li et al. https://doi.org/10.1016/j.trc.2021.103389
1936. Digital Footprints of Sensation Seeking R. Schoedel et al. https://doi.org/10.1027/2151-2604/a000342
1937. A New Mesoscopic Parameter Inverse Analysis Method of Hydraulic Concrete Based on the SVR-HGWO Intelligent Algorithm Q. Zhu et al. https://doi.org/10.3390/ma18184274
1938. Vegetation restoration dominated the variation of water use efficiency in China Y. Xue et al. https://doi.org/10.1016/j.jhydrol.2022.128257
1939. Shapelet-informed machine learning classifiers: A path towards precise identification of pulse-like ground motions F. Wani & J. Vemuri https://doi.org/10.1007/s12040-024-02314-2
1940. Multi-Reflectance-Spectroscopy, Part III: In-Line Monitoring of Milk Fat Globule Size via Sauter Diameter Using an Optical Sensor S. Boldt et al. https://doi.org/10.1177/00037028261440919
1941. Transient isogeometric heat conduction analysis of stationary fluid in a container V. Gupta et al. https://doi.org/10.1177/09544089221125718
1942. Comparative analysis of TGAN and other GAN models for synthetic earthquake data: a case study with data from Türkiye H. Urcan et al. https://doi.org/10.1007/s11069-025-07569-6
1943. Empirical Evaluation of Computer-Adaptive Alternate Short Forms for the Assessment of Anomia Severity W. Hula et al. https://doi.org/10.1044/2019_JSLHR-L-19-0213
1944. WRF4PALM v1.0: a mesoscale dynamical driver for the microscale PALM model system 6.0 D. Lin et al. https://doi.org/10.5194/gmd-14-2503-2021
1945. Deep learning versus gradient boosting machine for pan evaporation prediction A. Malik et al. https://doi.org/10.1080/19942060.2022.2027273
1946. Exploiting high-slip flow regimes to improve inference of glacier bed topography A. Morin et al. https://doi.org/10.1017/jog.2022.121
1947. The landscape pattern characteristics of urban built-up land significantly influence urban thermal comfort: Evidence from large cities in China C. Hu & H. Zeng https://doi.org/10.1016/j.scs.2025.106402
1948. A Computational Study of Green Tea Extracts and their Derivatives as Potential Inhibitors for Squalene Monooxygenase K. Mokgopa et al. https://doi.org/10.2174/0115734064280290240211170037
1949. Aircraft positioning using DGNSS technique for GPS and GLONASS data K. Krasuski & J. Ćwiklak https://doi.org/10.1108/SR-12-2018-0327
1950. Numerical study of dense powder flow in a rotating drum: Comparison of CFD to experimental measurements L. Chatre et al. https://doi.org/10.1016/j.powtec.2024.119981
1951. Complete offline tuning of the unscented Kalman filter L. Scardua & J. da Cruz https://doi.org/10.1016/j.automatica.2017.01.008
1952. Spectroscopic characterization of three fungicides using terahertz spectroscopy and DFT theory, combined with convolutional neural networks for quantitative analysis of tebuconazole L. Ma et al. https://doi.org/10.1016/j.saa.2025.126874
1953. Estimation of the Angles of a Robotic Arm with 7-Free Degrees Using an Improved Hybrid ESSA Algorithm I. Cizmeci et al. https://doi.org/10.1155/2023/9169050
1954. Medium-scale projection of reference evapotranspiration beyond available data using sequential deep learning models: a case study from Bangladesh D. Roy https://doi.org/10.1007/s00704-025-05861-w
1955. Dynamic Monitoring of the Largest Freshwater Lake in China Using a New Water Index Derived from High Spatiotemporal Resolution Sentinel-1A Data H. Tian et al. https://doi.org/10.3390/rs9060521
1956. Quality Assessment of Small Urban Catchments Stormwater Models: A New Approach Using Old Metrics L. David & T. Mota https://doi.org/10.3390/hydrology9050087
1957. Time-variant post-processing method for long-term numerical wind speed forecasts based on multi-region recurrent graph network Z. Duan et al. https://doi.org/10.1016/j.energy.2022.125021
1958. Developing a Machine Learning Approach for Estimating Urban NO2 Concentrations Using Multi-Source Remote Sensing Data M. Kukavica et al. https://doi.org/10.3390/smartcities9100166
1959. Assessment of the measurement statistics of model accuracy and the appropriate use of them (Case study: Interpolation of Precipitation in Fars province) A. Mirshafie et al. https://doi.org/10.61186/jsaeh.11.2.117
1960. Development of a fast and accurate PCRTM radiative transfer model in the solar spectral region X. Liu et al. https://doi.org/10.1364/AO.55.008236
1961. The employment of polynomial chaos expansion approach for modeling dissolved oxygen concentration in river B. Keshtegar et al. https://doi.org/10.1007/s12665-018-8028-8
1962. Climate Change Impact on Surface Water and Groundwater Recharge in Northern Thailand C. Petpongpan et al. https://doi.org/10.3390/w12041029
1963. Intelligent vehicle path tracking control strategy considering data-driven dynamic stable region constraints Y. Li et al. https://doi.org/10.1177/09544070231193178
1964. Feature engineering over complex architectures: A comparative analysis of machine learning models for short-term water demand forecasting S. Yaghoobzadeh & M. Naseri https://doi.org/10.2166/wpt.2026.393
1965. Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq K. Khosravi et al. https://doi.org/10.1016/j.compag.2019.105041
1966. CPUE standardization for Ethmalosa fimbriata (Bowdich, 1825) and Galeoides decadactylus (Bloch, 1795) using species distribution model Template Model Builder (sdmTMB) off the Central Gulf of Guinea E. Atem et al. https://doi.org/10.1016/j.seares.2026.102676
1967. Predicting the Corrosion Rate of Al and Mg Alloys Coated by Plasma Spraying Method with Machine Learning H. Özkavak & R. Tunay https://doi.org/10.55546/jmm.1459329
1968. A MACHINE-LEARNING-BASED MODEL FOR FORECASTING MEDICAL DEVICE FOREIGN TRADE T. BAYRAK https://doi.org/10.18038/estubtda.803546
1969. Evaluating compressive strength of concrete made with recycled concrete aggregates using machine learning approach V. Quan Tran et al. https://doi.org/10.1016/j.conbuildmat.2022.126578
1970. PRPOS: A Periodicity-Aware Resource Prediction Framework for Online Services Y. Liang et al. https://doi.org/10.3390/app152010967
1971. Robust intra-phase latitudinal ionospheric vertical total electron content forecasting with a stacked-JIT model E. Asamoah et al. https://doi.org/10.1016/j.asr.2026.06.068
1972. Application-aware deep learning for optical design: Enhancing transmittance prediction with a domain-specific loss function E. Ghapanvari et al. https://doi.org/10.1016/j.rio.2026.101127
1973. Artificial Bee Colony-Artificial Neural Network (ABC-ANN) Hybrid Algorithm’s Performance on the Modeling of Thermodynamic Properties of a Refrigerant Gas (R404a) S. Ozden https://doi.org/10.1080/08839514.2021.1994214
1974. Evaluating the Effects of Human Activity over the Last Decades on the Soil Organic Carbon Pool Using Satellite Imagery and GIS Techniques in the Nile Delta Area, Egypt E. Mohamed et al. https://doi.org/10.3390/su11092644
1975. Global assessments of the NCEP Ensemble Forecast System using altimeter data R. Campos et al. https://doi.org/10.1007/s10236-019-01329-4
1976. Bidirectional Long Short-term Neural Network Based on the Attention Mechanism of the Residual Neural Network (ResNet–BiLSTM–Attention) Predicts Porosity through Well Logging Parameters Y. Sun et al. https://doi.org/10.1021/acsomega.3c03247
1977. Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference station data R. Deo et al. https://doi.org/10.1016/j.renene.2017.09.078
1978. Micronutrients prediction via pXRF spectrometry in Brazil: Influence of weathering degree R. Andrade et al. https://doi.org/10.1016/j.geodrs.2021.e00431
1979. Dynamic Feature Selection for Solar Irradiance Forecasting Based on Deep Reinforcement Learning C. Lyu et al. https://doi.org/10.1109/TIA.2022.3206731
1980. Physics-informed multi-head LSTM-based predictive-prescriptive framework for process parameter optimization in fused deposition modeling S. Avro et al. https://doi.org/10.1007/s40964-026-01700-0
1981. The Sensitivity of Urban Heat Island to Urban Green Space—A Model-Based Study of City of Colombo, Sri Lanka D. Maheng et al. https://doi.org/10.3390/atmos10030151
1982. Fortified and freeze-dried kiwi fruit (Actinidia deliciosa): quality and sensory assessment N. Chakraborty et al. https://doi.org/10.1590/1981-6723.07719
1983. Automatic segmentation and quantification of hair follicle orientation S. Hussein https://doi.org/10.1016/j.imu.2020.100498
1984. Data-Driven Digital Twin Framework for Predictive Maintenance of Smart Manufacturing Systems T. Khan et al. https://doi.org/10.3390/machines13060481
1985. Improving Sports Outcome Prediction Process Using Integrating Adaptive Weighted Features and Machine Learning Techniques C. Lu et al. https://doi.org/10.3390/pr9091563
1986. DeepFogAQ: A fog-assisted decentralized air quality prediction and event detection system M. Şimsek et al. https://doi.org/10.1016/j.eswa.2024.123920
1987. Predicting soil organic carbon stocks in different layers of forest soils in the Czech Republic V. Oppong Sarkodie et al. https://doi.org/10.1016/j.geodrs.2023.e00658
1988. Decision-making support via early prediction for deep-tunnel drainage pumps: An LSTM-based two-stage framework S. Yang et al. https://doi.org/10.1016/j.jwpe.2026.110505
1989. Probabilistic yield forecasting of robusta coffee at the farm scale using agroclimatic and remote sensing derived indices L. Kouadio et al. https://doi.org/10.1016/j.agrformet.2021.108449
1990. A modelling framework for assessing the future water quality of Lake Diefenbaker under climate change J. Terry et al. https://doi.org/10.2166/wqrj.2026.076
1991. Nonpoint pollution loading forecast and assessment of optimal area of constructed wetland in dam watershed considering climate change scenario uncertainty H. Yi et al. https://doi.org/10.1016/j.ecoleng.2020.105910
1992. Hotel online reviews: creating a multi-source aggregated index N. Antonio et al. https://doi.org/10.1108/IJCHM-05-2017-0302
1993. Predictability of redox potential and oxygen status in managed aquifer recharge sites based on sensor data and regression techniques T. Turkeltaub et al. https://doi.org/10.1016/j.jhydrol.2025.133486
1994. Drought disaster monitoring and land use dynamics: identification of drought drivers using regression-based algorithms I. Orimoloye et al. https://doi.org/10.1007/s11069-022-05219-9
1995. A representativeness heuristic for mitigating spatial bias in existing soil samples for digital soil mapping G. Zhang & A. Zhu https://doi.org/10.1016/j.geoderma.2019.05.024
1996. Integration of Drone and Satellite Imagery Improves Agricultural Management Agility M. Ogungbuyi et al. https://doi.org/10.3390/rs16244688
1997. Efficient Monitoring Framework for Spoilage Prediction in Wheat Grain Warehouse J. Devi & A. Singhrova https://doi.org/10.1109/TAFE.2026.3685969
1998. Reliability-Based Load and Resistance Factor Design of an Energy Pile with CPT Data Using Machine Learning Techniques P. Kumar & P. Samui https://doi.org/10.1007/s13369-023-08253-2
1999. Dual Band Antenna Design and Prediction of Resonance Frequency Using Machine Learning Approaches M. Haque et al. https://doi.org/10.3390/app122010505
2000. Optimum Location of Outrigger–Belt Truss in High-Rise Buildings against Blast Loading Using Nonlinear Dynamic Analysis and Genetic Algorithm H. Ghanbari et al. https://doi.org/10.1061/JSDCCC.SCENG-2110
2001. Prediction of blasting-induced fragmentation in Meydook copper mine using empirical, statistical, and mutual information models N. Ghaeini et al. https://doi.org/10.1007/s12517-017-3189-4
2002. Estimating aboveground biomass of a mangrove plantation on the Northern coast of Vietnam using machine learning techniques with an integration of ALOS-2 PALSAR-2 and Sentinel-2A data T. Pham et al. https://doi.org/10.1080/01431161.2018.1471544
2003. A Multidimensional Reverse Interpolation Method and its Application in Solving the Multidimensional Fredholm Integral Equations S. Mirzaei & M. Amirfakhrian https://doi.org/10.1007/s40819-021-01096-1
2004. FORECASTING OF PESTICIDE USAGE IN PAKISTAN: AN APPLICATION OF THE UNIVARIATE ARIMA MODEL AND ARTIFICIAL NEURAL NETWORK M. Rabia et al. https://doi.org/10.31413/nat.v13i1.18546
2005. One‐Dimensional‐Convolutional Neural Network (1D‐CNN) Based Reliability Analysis of Foundation Over Cavity Incorporating the Effect of Simulated Noise K. Shubham et al. https://doi.org/10.1155/2024/9981433
2006. Regression-based models for the prediction of unconfined compressive strength of artificially structured soil L. Sharma & T. Singh https://doi.org/10.1007/s00366-017-0528-8
2007. A neural network approach on forecasting the engine emission using biodiesel fuel from fish oil based on injection pressure and engine operating parameters N. Van Tuan et al. https://doi.org/10.1016/j.engappai.2025.112628
2008. Hyperspectral Imaging with Enhanced Partial Least Squares Regression (PLSR) for Accurate Sago Powder Quality Evaluation P. Teo et al. https://doi.org/10.1080/00032719.2025.2592224
2009. Non‐destructive firmness assessment of ‘SunGold’ kiwifruit a three‐year study T. Sneddon et al. https://doi.org/10.1080/01140671.2024.2314496
2010. Enhancing food security: machine learning-based wheat yield prediction using remote sensing and climate data in Pakistan N. Ahmed et al. https://doi.org/10.1007/s00704-025-05475-2
2011. Evaluating rainfall estimates derived from soil moisture using soil hydraulic properties over the Korean Peninsula D. Kim et al. https://doi.org/10.1016/j.jhydrol.2025.134267
2012. Predictive Modeling of Urban Heat Stress Using Machine Learning: A 2050 UTCI-Based Assessment N. Arumugakani et al. https://doi.org/10.31127/tuje.1968300
2013. Characterizing High-Resolution Uneven Drought Conditions in Vietnam for More Reliable Hazard Assessment T. Le et al. https://doi.org/10.1007/s41748-026-01050-5
2014. Forecasting daily emergency ambulance service demand using biometeorological indexes H. Wong https://doi.org/10.1007/s00484-023-02435-1
2015. Evaluation of shaft angle to ball-to-target line as a predictor of horizontal delivery plane angle in the golf swing A. Morrison & J. Wells https://doi.org/10.1080/14763141.2024.2315253
2016. Calibration of intermittent water supply systems hydraulic models under data scarcity A. Leinæs et al. https://doi.org/10.2166/ws.2024.075
2017. Estimation of Leaf Area Index (LAI) in corn and soybeans using multi-polarization C- and L-band radar data M. Hosseini et al. https://doi.org/10.1016/j.rse.2015.09.002
2018. Weather-electricity demand relationships: A comparative analysis of linear regression and machine-learning approaches in Texas O. Rowland et al. https://doi.org/10.1016/j.segan.2026.102483
2019. Projected the Impacts of Climate Change on the Unconfined Aquifer Region, Western Iraq, Using LARS-WG and CMIP6 Scenarios H. Jalal et al. https://doi.org/10.1007/s41101-025-00410-y
2020. Evaluating the performance of RegCM4 in studies on irrigated and rainfed cotton crops A. Shikha et al. https://doi.org/10.1007/s12040-021-01705-z
2021. Modelling the Spatial Distribution of Soil Organic Carbon Using Machine Learning and Remote Sensing in Nevado de Toluca, Mexico C. Fusaro et al. https://doi.org/10.3390/geomatics5030043
2022. The computational age‐at‐death estimation from 3D surface models of the adult pubic symphysis using data mining methods A. Kotěrová et al. https://doi.org/10.1038/s41598-022-13983-8
2023. Cutting force and surface roughness prediction of Al 6065 T6 during turning operation using response surface methodology, machine learning, and simulation-based approach I. Daniyan et al. https://doi.org/10.1007/s00170-025-16556-x
2024. Quantitative-Structure-Activity-Relationship (QSAR) models for the reaction rate and temperature of nitrogenous organic compounds in supercritical water oxidation (SCWO) Z. Cheng et al. https://doi.org/10.1016/j.cej.2018.07.167
2025. Machine Learning-Based Prediction of Construction Labor Productivity Using Realistic Synthetic Datasets M. Yıldırım https://doi.org/10.1080/15578771.2026.2720806
2026. Estimation of Mangrove Canopy Cover Using Unmanned Aerial Vehicle (UAV) in Indramayu Regency, West Java N. Zahra et al. https://doi.org/10.1088/1755-1315/950/1/012032
2027. Comparison of rainfall-runoff models for climate change projection – case study of Citarum River Basin, Indonesia W. Hatmoko et al. https://doi.org/10.1088/1755-1315/423/1/012045
2028. Topographic and Climatic Controls on Depth–Duration–Frequency Curve Parameters in the Gargano Promontory (Southern Italy) G. Iemmolo et al. https://doi.org/10.3390/hydrology13070188
2029. Adaptive Network Based Fuzzy Inference System with Meta-Heuristic Optimizations for International Roughness Index Prediction H. Nguyen et al. https://doi.org/10.3390/app9214715
2030. Atmospheric CO2 fertilization effect on cereal yields in Morocco using the CARAIB dynamic vegetation model I. Loudiyi et al. https://doi.org/10.1016/j.eja.2024.127374
2031. Hybrid similarity based feature selection and cascade deep maxout fuzzy network for Autism Spectrum Disorder detection using EEG signal J. Singh & D. Kakkar https://doi.org/10.1016/j.compbiolchem.2024.108177
2032. Quantifying Uncertainty in Projections of Desertification in Central Asia Using Bayesian Networks J. Liu et al. https://doi.org/10.3390/rs17040665
2033. An Optimized CatBoost Model for Spatiotemporal Prediction of hmF2 in High-Latitude Regions T. Li et al. https://doi.org/10.3390/rs18152579
2034. Dynamic Neural Network Modelling of Soil Moisture Content for Predictive Irrigation Scheduling O. Adeyemi et al. https://doi.org/10.3390/s18103408
2035. Anthocyanins estimation in homogeneous bean landrace (<em>Phaseolus vulgaris</em> L.) using probabilistic representation and convolutional neural networks J. Morales-Reyes et al. https://doi.org/10.4081/jae.2023.1421
2036. A reinforcement learning-based approach for imputing missing data S. Awan et al. https://doi.org/10.1007/s00521-022-06958-3
2037. Application of non-linear partial least squares analysis on prediction of biomass of maize plants using hyperspectral images D. Ma et al. https://doi.org/10.1016/j.biosystemseng.2020.09.002
2038. Improving GSMaP V06 precipitation products over the Upper Tocantins River basin in the Brazilian Cerrado, based on local rain-gauge network R. Pereira et al. https://doi.org/10.1007/s00704-022-03985-x
2039. Using Multi-decadal Satellite Records to Identify Environmental Drivers of Fire Severity Across Vegetation Types D. Rodriguez-Cubillo et al. https://doi.org/10.1007/s41976-022-00070-9
2040. Evolution of market concentration and competition in the microfinance industry of Bangladesh M. Mia https://doi.org/10.1108/IJSE-10-2016-0281
2041. Optimizing Predictor Variables in Artificial Neural Networks When Forecasting Raw Material Prices for Energy Production M. Matyjaszek et al. https://doi.org/10.3390/en13082017
2042. Analysis of different hypotheses for modeling air–water exchange and temperature evolution in a tropical reservoir J. Alzate-Gómez et al. https://doi.org/10.2166/wcc.2023.567
2043. Liming and soil texture affect the miscible displacement of phosphorus from organic and mineral sources in tropical oxisols R. de Sousa et al. https://doi.org/10.1016/j.scitotenv.2024.178341
2044. Advanced machine learning for predicting groundwater decline and drought in the Rabat–Salé–Kénitra region, Morocco A. Elmotawakkil & N. Enneya https://doi.org/10.2166/hydro.2024.328
2045. Spatiotemporal patterns and drivers of vegetation greenness and resilience in China's open-pit coal mines over the past four decades H. Wang et al. https://doi.org/10.1016/j.jclepro.2026.149429
2046. Data-driven prediction of organic rejection in forward osmosis: Incorporating hydrophobic and dynamic transport effects Y. Wu et al. https://doi.org/10.1016/j.cej.2026.180789
2047. The Role of Financial and Macroeconomic Factors in Credit Risk Prediction: A Machine Learning Approach for EU Countries O. Özdemi̇r et al. https://doi.org/10.15388/Ekon.2026.105.3.4
2048. Bioclimatic inference based on mammal community using machine learning regression models: perspectives for paleoecological studies P. Linchamps et al. https://doi.org/10.3389/fevo.2023.1178379
2049. Validation of ocean color remote sensing reflectance data: Analysis of results at European coastal sites F. Mélin https://doi.org/10.1016/j.rse.2022.113153
2050. Use of Optimally Pruned Extreme Learning Machine (OP-ELM) in Forecasting Dissolved Oxygen Concentration (DO) Several Hours in Advance: a Case Study from the Klamath River, Oregon, USA S. Heddam https://doi.org/10.1007/s40710-016-0172-0
2051. Estimation of groundwater quality using an integration of water quality index, artificial intelligence methods and GIS: Case study, Central Mediterranean Region of Turkey S. Taşan https://doi.org/10.1007/s13201-022-01810-4
2052. Main sources of variability and non-determinism in AD software: taxonomy and prospects to handle them M. Alcon et al. https://doi.org/10.1007/s11241-023-09405-1
2053. Effects of Aerosols on Gross Primary Production from Ecosystems to the Globe Y. Shu et al. https://doi.org/10.3390/rs14122759
2054. Forecasting road traffic accidents in India: a SARIMAX approach incorporating COVID-19 effects S. Singh & V. Singh https://doi.org/10.1080/17457300.2025.2541662
2055. Spatial downscaling of 3-hourly precipitation forecast data at river basin scale J. Mendes & R. Maia https://doi.org/10.1007/s00703-019-00678-5
2056. Individual Tree Parameters Estimation for Chinese Fir (Cunninghamia lanceolate (Lamb.) Hook) Plantations of South China Using UAV Oblique Photography: Possibilities and Challenges T. Yin et al. https://doi.org/10.1109/JSTARS.2020.3038819
2057. New double decomposition deep learning methods for river water level forecasting A. Ahmed et al. https://doi.org/10.1016/j.scitotenv.2022.154722
2058. A Machine Learning-Based Modeling Approach for Dye Removal Using Modified Natural Adsorbents B. Uzbas & S. Kocaman https://doi.org/10.1021/acs.jcim.5c01016
2059. Probabilistic spatiotemporal forecasting of wind speed based on multi-network deep ensembles method G. Liu et al. https://doi.org/10.1016/j.renene.2023.03.094
2060. A hybrid deep learning framework for multivariate energy forecasting and peak load prediction in electric vehicle charging infrastructure M. Waqar et al. https://doi.org/10.1016/j.apenergy.2025.126964
2061. A New Paradigm in Flood Management: Hydrological, Hydraulic, and Deep Learning Methods for Flood Routing M. Sarıgöl et al. https://doi.org/10.1007/s11269-026-04865-z
2062. New accurate approximation of the Einstein Relation for heavily-doped semiconductor devices A. AlQurashi & C. Selvakumar https://doi.org/10.1016/j.sse.2020.107869
2063. Impact of Nutrient Limitation on Nezara viridula Development: Validation of a Stage‐Structured Degree‐Day Model in Outdoor and Greenhouse Environments Using Citizen Science Data R. Moerkens et al. https://doi.org/10.1111/jen.13464
2064. Explainable ML for Irrigation Water Quality Prediction in the Sedrata Aquifer, Plain (Algeria) F. Nadour et al. https://doi.org/10.3390/w18172215
2065. Modeling building carbon emissions by using MARS algorithm: A case of Istanbul S. Kangalli Uyar et al. https://doi.org/10.1016/j.buildenv.2024.111768
2066. Machine Learning-Driven Techno-Economic Uncertainty Analysis in Batch Pharmaceutical Manufacturing D. Ordonez et al. https://doi.org/10.1021/acsomega.5c09455
2067. Study of 2D contaminant transport with depth varying input source in a groundwater reservoir M. Singh et al. https://doi.org/10.2166/ws.2021.010
2068. Impacts of land surface temperature and ambient factors on near-surface air temperature estimation: A multisource evaluation using SHAP analysis S. Li et al. https://doi.org/10.1016/j.scs.2025.106257
2069. Smartphone-based colorimetric sensing with reference calibration and ensemble machine learning for enhanced detection of nitrite and ammonium ions T. Quoc et al. https://doi.org/10.1016/j.aca.2026.345097
2070. Creating a Thermally Comfortable Environment for Public Spaces in Coastal Villages Considering Both Spatial Genetics and Landscape Elements Y. Pang et al. https://doi.org/10.3390/su17062488
2071. P-Wave Velocity Log Simulation for Petroelastic Inversion Using Gardner’s Equation, Neural Networks And Ensemble Methods Based on Trees: A Case Study of the Santos Basin, Brazil C. Carvalho et al. https://doi.org/10.22564/brjg.v42i2.2315
2072. Exploring the Influence of Tropical Cyclones on Regional Air Quality Using Multimodal Deep Learning Techniques M. Younis et al. https://doi.org/10.3390/s24216983
2073. The potential of nonparametric model in foundation bearing capacity prediction S. Jabbar et al. https://doi.org/10.1007/s00521-017-2916-9
2074. Physics-Based Machine Learning Framework for Predicting Structure-Property Relationships in DED-Fabricated Low-Alloy Steels A. Rahman et al. https://doi.org/10.3390/met15090965
2075. Assessment of agricultural land suitability using GIS and fuzzy analytical hierarchy process approach in Ranchi District, India S. Sengupta et al. https://doi.org/10.1080/10106049.2022.2076925
2076. Geophysical Data Inversion in a Gold-Rich Porphyry System: A Case Study of the Dalli Deposit, Iran K. Moshtaghian et al. https://doi.org/10.1007/s11053-023-10165-9
2077. Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks O. Karadut et al. https://doi.org/10.1021/acsomega.6c03040
2078. Application of a Partial Convolutional Neural Network for Estimating Geostationary Aerosol Optical Depth Data Y. Lops et al. https://doi.org/10.1029/2021GL093096
2079. Nonlinear biotic ligand model for assessing alleviation effects of Ca, Mg, and K on Cd toxicity to soybean roots B. Chen et al. https://doi.org/10.1007/s10646-017-1823-2
2080. Self-labelling of tugboat operation using unsupervised machine learning and intensity indicator J. Hadi et al. https://doi.org/10.1016/j.martra.2023.100082
2081. Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization N. Mehdiyev et al. https://doi.org/10.1007/s12559-024-10294-0
2082. FPUNet: A Fourier-Enhanced U-Net for Robust 2-D Phase Unwrapping of Noisy InSAR Interferograms Y. He et al. https://doi.org/10.3390/rs18050808
2083. Modeling the Multisector Business Interruption Ratio in Earthquake-Struck Regions Q. Mao et al. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000964
2084. Integrated Seasonal Drought Risk Assessment Under Climate and Land Use Changes for Agricultural Areas Upstream of Pasak Reservoir, Thailand T. Promping & T. Tingsanchali https://doi.org/10.3390/limnolrev26020025
2085. Mitigation of multipath fading in indoor radiometric fingerprinting systems M. Agel et al. https://doi.org/10.1016/j.compeleceng.2018.11.002
2086. A subseasonal-to-seasonal runoff forecasting framework under uncertainty: application of numerical weather predictions and a Bayesian maximum entropy-based data fusion technique M. Soltani et al. https://doi.org/10.2166/hydro.2025.022
2087. Using Unmanned Aerial Systems (UAS) to assay mangrove estuaries on the Pacific coast of Costa Rica A. Yaney-Keller et al. https://doi.org/10.1371/journal.pone.0217310
2088. Exploring the dual impact of AI in post-entry language assessment: Potentials and pitfalls T. Zhang et al. https://doi.org/10.1017/S0267190525000030
2089. Towards efficient and effective renewable energy prediction via deep learning Z. Khan et al. https://doi.org/10.1016/j.egyr.2022.08.009
2090. Effect of Climate Change on Soil Erosion in a Mountainous Mediterranean Catchment (Central Pindus, Greece) S. Stefanidis & D. Stathis https://doi.org/10.3390/w10101469
2091. Using “big data” and non-linear machine learning to infer groundwater contamination mechanisms across a spatially extensive, geologically heterogeneous region I. Petculescu et al. https://doi.org/10.1016/j.wroa.2025.100475
2092. Learning-Based Matched Representation System for Job Recommendation S. Alsaif et al. https://doi.org/10.3390/computers11110161
2093. Influence of the ENSO and Monsoonal Season on Long-Term Wind Energy Potential in Malaysia A. Albani et al. https://doi.org/10.3390/en11112965
2094. Gravity Predictions in Data-Missing Areas Using Machine Learning Methods Y. Liu et al. https://doi.org/10.3390/rs16224173
2095. STEEP: A remotely-sensed energy balance model for evapotranspiration estimation in seasonally dry tropical forests U. Bezerra et al. https://doi.org/10.1016/j.agrformet.2023.109408
2096. Conjugation of Artificial Neural Networks with Nature-Inspired Optimization Algorithms for Predicting the Economic Growth of the Top Oil-Producing Countries in Africa B. Yahaya et al. https://doi.org/10.1007/s10614-025-11104-x
2097. Sandy beach erosion: impacts and adaptation strategies in Thailand H. Thepsiriamnuay & N. Pumijumnong https://doi.org/10.1007/s10668-024-04763-7
2098. Chemometric modeling of larvicidal activity of plant derived compounds against zika virus vectorAedes aegypti: application of ETA indices P. De et al. https://doi.org/10.1039/C7RA13159C
2099. DP-GAN+B: A lightweight generative adversarial network based on depthwise separable convolutions for generating CT volumes X. Xing et al. https://doi.org/10.1016/j.compbiomed.2024.108393
2100. AI-powered ultrasound radiofrequency analysis for non-invasive pediatric liver fat quantification G. Choi et al. https://doi.org/10.1038/s41598-026-37862-8
2101. Interpretable machine learning framework for air quality prediction in Istanbul using Shapley additive explanations (SHAP) E. Birinci et al. https://doi.org/10.1007/s00477-026-03168-4
2102. Artificial intelligence-based delay prediction models for signalized intersections in urban areas A. Maltaş et al. https://doi.org/10.1139/cjce-2025-0110
2103. Parameterization of particle formation rates in distinct atmospheric environments X. Li et al. https://doi.org/10.5194/ar-3-271-2025
2104. A Data-Driven Approach for Studying the Influence of Carbides on Work Hardening of Steel M. Vittorietti et al. https://doi.org/10.3390/ma15030892
2105. Performance Comparison of LSTM and ESN Models in Time-Series Prediction of Solar Power Generation Y. Joo et al. https://doi.org/10.3390/su17198538
2106. Bed breakage function modeling of a cement vertical roller mill using SHAP-XGBoost: a “conscious lab of bed grinding principle” approach R. Fatahi et al. https://doi.org/10.1016/j.measurement.2026.122741
2107. Prediction of soil macro- and micro-elements in sieved and ground air-dried soils using laboratory-based hyperspectral imaging technique M. Malmir et al. https://doi.org/10.1016/j.geoderma.2018.12.049
2108. CNN-based qualitative detection of bone mineral density via diagnostic CT slices for osteoporosis screening C. Tang et al. https://doi.org/10.1007/s00198-020-05673-w
2109. Simulation of mid-latitude winter storms over the North Atlantic Ocean: impact of boundary layer parameterization schemes P. Pradhan et al. https://doi.org/10.1007/s00382-019-04962-3
2110. Solar module emulator based on a low-cost microcontroller A. Boucharef et al. https://doi.org/10.1016/j.measurement.2021.110275
2111. Determining hypertensive patients’ beliefs towards medication and associations with medication adherence using machine learning methods F. Aziz et al. https://doi.org/10.7717/peerj.8286
2112. Designing a Fuzzy Adaptive Neural Network Leveraging a Feature Self-Enhancement Unit and Statistical Selection Methods Z. Wang & Z. Fu https://doi.org/10.3390/electronics12102281
2113. AI-enabled inclusive employment in industry 5.0 bibliometric trends and forecasting for persons with hearing disability A. Yadav et al. https://doi.org/10.1007/s43621-026-03126-8
2114. A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping O. Ghorbanzadeh et al. https://doi.org/10.1007/s11069-018-3449-y
2115. Dynamic modeling of the growth of spoilage fungi on sweet cherries under fluctuating temperatures S. Xing et al. https://doi.org/10.3389/fmicb.2026.1858080
2116. Assessment of Feature Selection Methods for Machine Learning-Based Chlorophyll-a Retrieval Across Optical Water Types B. Arabi et al. https://doi.org/10.3390/rs18142381
2117. Ensemble learning framework for predicting close proximity tire–pavement noise on expressways W. Cho et al. https://doi.org/10.1016/j.cscm.2026.e06379
2118. Agronomic variables outperform multispectral indices for individual plant yield prediction in Andean quinoa S. Pizarro et al. https://doi.org/10.1016/j.rsase.2026.102027
2119. A novel synergistic fibroblast optimization based Kalman estimation model for forecasting time-series data T. Dhivyaprabha et al. https://doi.org/10.1007/s12530-018-9217-0
2120. Interpretable prediction of zinc ion location in proteins with ZincSight G. Mechtinger et al. https://doi.org/10.1002/pro.70350
2121. Temporal Convolutional Networks with RNN approach for chaotic time series prediction H. Dudukcu et al. https://doi.org/10.1016/j.asoc.2022.109945
2122. Objective evaluation of 35 heart rate variability parameters for predicting takeover performance in conditionally automated driving N. Zhang et al. https://doi.org/10.1016/j.ergon.2025.103699
2123. FPGA‐Based GRU Accelerator for Streaming Data Processing D. Hameed & A. Zyarah https://doi.org/10.1002/for.70217
2124. Integrated global to regional atmosphere predictors for drought modeling in Iran F. Mirzaei et al. https://doi.org/10.1007/s00704-026-06124-y
2125. Thermal performance of a novel solar thermal facade system in a hot-summer and cold-winter zone Y. A et al. https://doi.org/10.1016/j.solener.2020.04.050
2126. Field validation of dynamic mechanical torque measurements using fiber-optic strain sensors for geared wind turbines U. Gutierrez-Santiago et al. https://doi.org/10.1007/s10010-025-00793-3
2127. QbD-Based Design Space Development for Honey-Containing Traditional Chinese Medicine Tablets Assisted by the SeDeM Expert System and Machine Learning X. Deng et al. https://doi.org/10.3390/pharmaceutics18081014
2128. Machine learning based online fault prognostics for nonstationary industrial process via degradation feature extraction and temporal smoothness analysis Y. Hu et al. https://doi.org/10.1007/s11771-021-4848-x
2129. Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process H. Pourghasemi et al. https://doi.org/10.1016/j.gsf.2020.03.005
2130. Manufacturing and modeling of helix-wrapped pneumatic artificial muscles A. El-Sayed et al. https://doi.org/10.1088/1361-665X/ae05dc
2131. Kriging methods with auxiliary nighttime lights data to detect potentially toxic metals concentrations in soil J. Zhen et al. https://doi.org/10.1016/j.scitotenv.2018.12.330
2132. Variable-Bandwidth Self-Convergent Variational Mode Decomposition and its Application to Fault Diagnosis of Rolling Bearing Y. Lv et al. https://doi.org/10.1109/TIM.2024.3370808
2133. Imputation of missing data from offshore wind farms using spatio-temporal correlation and feature correlation C. Sun et al. https://doi.org/10.1016/j.energy.2021.120777
2134. Predictive modeling of the potentially hazardous psychrotolerant Bacillus cereus group in fried rice M. Kang et al. https://doi.org/10.1016/j.foodres.2025.115698
2135. Diseño de un sistema de monitoreo térmico para la asistencia en la deposición de material en WAAM U. Muñoz Ramirez https://doi.org/10.37511/apuntesci.v4n2a4
2136. Analysing and quantitative examination for development of predictive frameworks in residential construction waste by using machine learning models A. Gulghane et al. https://doi.org/10.1007/s42107-025-01424-6
2137. Quartile Regression and Ensemble Models for Extreme Events of Multi-Time Step-Ahead Monthly Reservoir Inflow Forecasting J. Weekaew et al. https://doi.org/10.3390/w16233388
2138. Comparative analysis of the measurement methods for the supraharmonic range T. Mendes et al. https://doi.org/10.1016/j.ijepes.2019.105801
2139. Indoor Air Design Parameters of Air Conditioners for Mold-Prevention and Antibacterial in Island Residential Buildings X. Zhang et al. https://doi.org/10.3390/ijerph17197316
2140. Artificial intelligence-based fast and efficient hybrid approach for spatial modelling of soil electrical conductivity M. Ghorbani et al. https://doi.org/10.1016/j.still.2018.09.012
2141. Bayesian-optimized BiLSTM-U-Net framework for urban flood prediction with spatio-temporal feature integration X. Yao et al. https://doi.org/10.1016/j.jhydrol.2026.135175
2142. Constraining Galaxy-Halo connection using machine learning A. Jana & L. Samushia https://doi.org/10.1016/j.ascom.2024.100883
2143. Enhancing harmful algal bloom predictions through integrated modeling of turbidity and nutrient dynamics in monsoon climate reservoirs D. Kim & S. Chung https://doi.org/10.1016/j.jenvman.2025.125291
2144. Residual-hybrid dynamic response-surface/machine-learning framework for predicting malachite green removal and biodegradation by a bacterial consortium E. Sakr et al. https://doi.org/10.1186/s13036-026-00663-8
2145. Spectral decomposition of iron-sulfur clusters I. Betinol et al. https://doi.org/10.1016/j.ab.2021.114269
2146. The impact of oxides of cementitious materials on mortar strength: A machine learning perspective N. Sathiparan https://doi.org/10.1016/j.scp.2025.102178
2147. Non-Linear Input Variable Selection Approach Integrated With Non-Tuned Data Intelligence Model for Streamflow Pattern Simulation S. Hadi et al. https://doi.org/10.1109/ACCESS.2019.2943515
2148. Assessment of plant density for barley and wheat using UAV multispectral imagery for high-throughput field phenotyping N. Wilke et al. https://doi.org/10.1016/j.compag.2021.106380
2149. A novel Hybrid Wavelet-Locally Weighted Linear Regression (W-LWLR) Model for Electrical Conductivity (EC) Prediction in Surface Water I. Ahmadianfar et al. https://doi.org/10.1016/j.jconhyd.2020.103641
2150. LSTM-based deep learning model for alkali activated binder mix design of clay soils M. Arab et al. https://doi.org/10.1007/s41062-024-01781-2
2151. Optimation of Crawler Speeds Measurement Using Inductive Proximity for Autonomous Combine Harvester S. Sutisna et al. https://doi.org/10.1088/1755-1315/542/1/012029
2152. Investigation of the Unbalance Estimation for a Double U-Joint Driveshaft Under Misalignment Uncertainty and Decreased Stiffness M. Belhorma et al. https://doi.org/10.1007/s42417-023-00942-4
2153. Hydrodynamic Modelling of Bidong Island Vicinity Waters N. Daud & M. Akhir https://doi.org/10.4236/ojms.2015.53026
2154. Correcting Satellite Precipitation Data and Assimilating Satellite-Derived Soil Moisture Data to Generate Ensemble Hydrological Forecasts within the HBV Rainfall-Runoff Model M. Ciupak et al. https://doi.org/10.3390/w11102138
2155. Capsules TCN Network for Urban Computing and Intelligence in Urban Traffic Prediction D. Li et al. https://doi.org/10.1155/2020/6896579
2156. The Development and Field Evaluation of an IoT–LoRa-Based Water-Quality-Monitoring and Aeration-Actuation System for Tilapia Cage Farming P. Sangkaphet et al. https://doi.org/10.3390/app16115308
2157. Prediction of agricultural drought behavior using the Long Short-Term Memory Network (LSTM) in the central area of the Gulf of Mexico F. Salas-Martínez et al. https://doi.org/10.1007/s00704-024-05100-8
2158. Modeling engagement with a digital behavior change intervention (HeartSteps II): An exploratory system identification approach S. De La Torre et al. https://doi.org/10.1016/j.jbi.2024.104721
2159. Determination of ionization/protonation constant values of some guanine derivative drugs by traditional/ green RPLC and UV–Vis spectrophotometric methods Y. Doğan Daldal & E. Çubuk Demiralay https://doi.org/10.1016/j.molliq.2024.125450
2160. Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions H. Apaydin et al. https://doi.org/10.1016/j.jhydrol.2021.126506
2161. Engine-in-the-Loop in practical application: A sensitivity study toward the influence of test bench parameters A. Wahl et al. https://doi.org/10.1177/09544070221085971
2162. Valley-Forecast: Forecasting Coccidioidomycosis incidence via enhanced LSTM models trained on comprehensive meteorological data L. Huender et al. https://doi.org/10.1016/j.jbi.2025.104774
2163. Modeling Landscape Change Effects on Stream Temperature Using the Soil and Water Assessment Tool M. Mustafa et al. https://doi.org/10.3390/w10091143
2164. Optimizing reservoir operation to avoid downstream physical habitat loss using coupled ANFIS- metaheuristic model M. Sedighkia et al. https://doi.org/10.1007/s12145-021-00671-w
2165. High accuracy prediction of Thai rice glycemic index using machine learning Y. Durmus https://doi.org/10.1080/23311932.2024.2411032
2166. A long lead time forecast model applying an ensemble approach for managing the great Karun multi-reservoir system E. Mostaghimzadeh et al. https://doi.org/10.1007/s13201-023-01924-3
2167. Climate data verification for assessing climate change in Almaty region of the Republic of Kazakhstan K. Kyrgyzbay et al. https://doi.org/10.1016/j.cliser.2023.100423
2168. The predicted effectiveness of thermal condition mitigation strategies for a climate-resilient archaeological park F. Binarti et al. https://doi.org/10.1016/j.scs.2021.103457
2169. Guangzhou Housing Price Prediction Based On Machine Learning Regression Models Z. Huang et al. https://doi.org/10.54097/hset.v44i.7355
2170. Adaptive Broad Echo State Network for Nonstationary Time Series Forecasting W. Liu et al. https://doi.org/10.3390/math10173188
2171. Parametric machine learning integrated approach for assessing environmental and engine variables on fuel consumption and carbon intensity O. Yuksel et al. https://doi.org/10.1080/20464177.2025.2499346
2172. A bio-inspired artificial intelligence framework leveraging remote sensing for groundwater storage modeling in climate-stressed regions A. Elmotawakkil et al. https://doi.org/10.1016/j.ige.2026.04.001
2173. Numerical analysis on the cooling performance of a ventilated Trombe wall combined with venetian blinds in an office building Z. Hu et al. https://doi.org/10.1016/j.enbuild.2016.05.016
2174. Recommendation system techniques and related issues: a survey P. Kumar & R. Thakur https://doi.org/10.1007/s41870-018-0138-8
2175. Reliability‐based state parameter liquefaction probability prediction using soft computing techniques K. Kumar et al. https://doi.org/10.1002/gj.5049
2176. Evaluation of weather-productivity models of construction labour for tropics A. Al-Refaie et al. https://doi.org/10.1108/BEPAM-03-2022-0040
2177. Characterization of salt wedge intrusion process in a geographically complex microtidal deltaic estuarine system F. Torres-Bejarano et al. https://doi.org/10.1016/j.jsames.2023.104646
2178. Performance Evaluation of Machine Learning Algorithms for Predicting Organic Photovoltaic Efficiency S. Mirza & Y. Simon https://doi.org/10.70322/ces.2025.10016
2179. Prediction of the antibacterial activity of garlic extract on E. coli, S. aureus and B. subtilis by determining the diameter of the inhibition zones using artificial neural networks D. Atsamnia et al. https://doi.org/10.1016/j.lwt.2017.04.053
2180. Integrating lithofacies and well logging data into smooth generalized additive model for improved permeability estimation: Zubair formation, South Rumaila oil field W. J Al-Mudhafar https://doi.org/10.1007/s11001-018-9370-7
2181. Modeling Short-Term Passenger Flows in Metro and Bus Systems Using Meteorological Data: Deep Learning Model Comparisons C. Yazıcıoğlu & A. Akgüngör https://doi.org/10.3390/app15116260
2182. A Comparative Analysis of IMUs and Optical Systems in Layup Shot Biomechanics N. Alkhalaf et al. https://doi.org/10.3390/app15073847
2183. Usability of first molar teeth measurements for age and sex estimation in cone-beam computed tomography images N. KOCAK TOPBAS & A. OKKESİM https://doi.org/10.31020/mutftd.958620
2184. Comparative Evaluation of Estimated Private Rates of Return to General and Vocational Upper Secondary Education in Greece: Mincer and Machine Learning Approaches A. Velaora et al. https://doi.org/10.3390/educsci16040662
2185. Differential Effects of Soil Moisture and Air Temperature on Vegetation Dynamics in Northwest China’s Warming and Wetting Region: An LSTM Modeling Approach Y. Si et al. https://doi.org/10.3390/plants15101542
2186. Deep Learning Strategies for Labeling and Accuracy Optimization in Microcontroller Performance Screening N. Bellarmino et al. https://doi.org/10.1109/TCAD.2024.3436542
2187. Predictive analysis of engine power limitations for fuel reduction in a tanker ship using a rule-based machine learning technique A. Ersoy et al. https://doi.org/10.1016/j.jclepro.2025.145535
2188. Prediction of the Continuous Probability of Sand Screenout Based on a Deep Learning Workflow L. Hou et al. https://doi.org/10.2118/209192-PA
2189. Aerosols modulate East Asian surface temperature: unique cloud-radiation feedback and species-dependent effects D. Chen et al. https://doi.org/10.1038/s44407-025-00040-7
2190. A pattern-oriented model for assessing effects of weather and freshwater discharge on black coral (Antipathes fiordensis) distribution in a fjord W. Jiang et al. https://doi.org/10.1016/j.ecolmodel.2015.02.020
2191. Influence of land cover, slope, and aspect on the vertical accuracy of SPOT DEM at selected sites in Nigeria P. Nwilo et al. https://doi.org/10.1007/s12518-021-00404-0
2192. Exploring the power of data-driven models for groundwater system conceptualization: a case study of the Grazer Feld Aquifer, Austria A. Kokimova et al. https://doi.org/10.1007/s10040-024-02830-x
2193. A data-driven method to predict future bottlenecks in a remanufacturing system with multi-variant uncertainties Z. Xue et al. https://doi.org/10.1007/s11771-022-4906-z
2194. Evaluating the Cost-Effectiveness of Cervical Cancer Screening and Treatment in Western Romania I. Petre et al. https://doi.org/10.3390/curroncol32060336
2195. How spatial scales enhance prediction: an interpretable multi-scale framework for bike-sharing demand prediction J. Zhu et al. https://doi.org/10.1080/10095020.2025.2522149
2196. Sensitivity analysis in digital pathology: Handling large number of parameters with compute expensive workflows J. Gomes et al. https://doi.org/10.1016/j.compbiomed.2019.03.006
2197. Monthly to seasonal rainfall erosivity over Italy: Current assessment by empirical model and future projections by EURO-CORDEX ensemble R. Padulano et al. https://doi.org/10.1016/j.catena.2023.106943
2198. Wavelet-SARIMA-Transformer: a hybrid model for rainfall forecasting J. Saikia et al. https://doi.org/10.1007/s00704-026-06032-1
2199. Predicting Surfactant Oil–Water Interfacial Tension Using Gated Message-Passing Graph Neural Networks S. Liu et al. https://doi.org/10.1021/acsomega.6c03262
2200. Prediction of the Growth Rates of Pseudomonas sp. in Seafood Based on Artificial Neural Network (ANN) Model I. Genç https://doi.org/10.1080/10498850.2023.2219675
2201. Attentive Contextual Attention for Cloud Removal W. Huang et al. https://doi.org/10.1109/TGRS.2024.3472645
2202. An improved long short-term memory network for streamflow forecasting in the upper Yangtze River S. Zhu et al. https://doi.org/10.1007/s00477-020-01766-4
2203. Modeling post-earthquake business recovery time: An analytical framework G. Cremen et al. https://doi.org/10.1016/j.ijdrr.2019.101328
2204. Analysis of the Fruit Drop Rate Caused by Typhoons Using Meteorological Data S. Choi et al. https://doi.org/10.3390/agriculture13091800
2205. Short- and long-term weather prediction based on a hybrid of CEEMDAN, LMD, and ANN S. Gyamerah et al. https://doi.org/10.1371/journal.pone.0304754
2206. Deep learning with spatio-temporal conditioning improves global subseasonal precipitation forecasts G. Noh & K. Ahn https://doi.org/10.1038/s41612-026-01430-8
2207. Nexus Between Baltic Dry Index and Oil Price: New Evidence from Linear and Nonlinear ARDL Approaches T. Nguyen et al. https://doi.org/10.3390/economies14030086
2208. EFAR-MMLA: An Evaluation Framework to Assess and Report Generalizability of Machine Learning Models in MMLA P. Chejara et al. https://doi.org/10.3390/s21082863
2209. A pilot study of gaseous pollutants' measurement (NO2, SO2, NH3, HNO3 and O3) in Abidjan, Côte d'Ivoire: contribution to an overview of gaseous pollution in African cities J. Bahino et al. https://doi.org/10.5194/acp-18-5173-2018
2210. Hybrid framework of deep extreme learning machine (DELM) based on sparrow search algorithm for non-stationary wave prediction Z. Su et al. https://doi.org/10.1016/j.oceaneng.2024.118993
2211. Predicting EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L) Utilities from Older People’s Quality of Life Brief Questionnaire (OPQoL-Brief) Scores B. Kaambwa & J. Ratcliffe https://doi.org/10.1007/s40271-017-0259-3
2212. Seismogenic index improves deep learning performance for seismicity rate forecasting in Utah FORGE and EGS Collab projects S. Zhang et al. https://doi.org/10.1093/gji/ggag190
2213. Dual-stream learning with inverted transformer and BiGRU for rolling bearing remaining useful life prediction S. Wu et al. https://doi.org/10.1038/s41598-026-60290-7
2214. Identifying facile material descriptors for Charpy impact toughness in low-alloy steel via machine learning Y. Chen et al. https://doi.org/10.1016/j.jmst.2022.05.051
2215. Temporal resolution enhancement of NDVI time series using machine learning approaches S. Park et al. https://doi.org/10.1007/s40808-025-02551-4
2216. Volunteered geographic information quality assessment using trust and reputation modelling in land administration systems in developing countries K. Moreri et al. https://doi.org/10.1080/13658816.2017.1409353
2217. A hybrid machine learning approach for housing price prediction: the stacking regressor method Ö. Erbulut & Z. Çolak https://doi.org/10.1108/IJHMA-01-2025-0010
2218. Vis-NIR Spectroscopy and Machine Learning for Prediction of Soil Fertility Indicators and Fertilizer Recommendation in Andean Highland and Rainforest Agroecosystems S. Pizarro et al. https://doi.org/10.3390/rs18091331
2219. Interannual variability of Indonesian throughflow in the Flores Sea P. Putriani et al. https://doi.org/10.1088/1755-1315/278/1/012064
2220. In-Depth Analysis and Prediction of Coupling Metrics of Open Source Software Projects M. Saini et al. https://doi.org/10.4018/JITR.301267
2221. Unlocking waste potential: A neural network approach to forecasting sustainable acetaldehyde production from ethanol upcycling in biomass waste gasification Y. Ayub et al. https://doi.org/10.1016/j.energy.2024.131482
2222. Predicting water quality associated with land cover change in the Grootdraai Dam catchment, South Africa A. du Plessis et al. https://doi.org/10.1080/02508060.2015.1067752
2223. Which Climate Model Evaluation Methods Can Consistently Select Skillful Models from the CMIP6 Ensemble? N. Gnatiuk et al. https://doi.org/10.24057/2071-9388-2025-3694
2224. Improved Simultaneous Algebraic Reconstruction Technique Algorithm for Positron-Emission Tomography Image Reconstruction via Minimizing the Fast Total Variation A. Boudjelal et al. https://doi.org/10.1016/j.jmir.2017.09.005
2225. Pedestrian-Oriented Microclimate Optimization for Urban Plazas: Integrating Movement Patterns with Thermal Comfort Simulation H. Huang et al. https://doi.org/10.3390/buildings16101874
2226. Relaxation factor optimization based on cuckoo search algorithm for limited – Angle CT A. Gomeri et al. https://doi.org/10.1016/j.bspc.2021.103067
2227. Forecasting short-term rainfall patterns in arid and semi-arid regions using machine learning and deep learning models: a case study from Morocco A. Elmotawakkil et al. https://doi.org/10.1007/s00704-025-05677-8
2228. Bayesian-Optimized Learning on Heterogeneous Multipartite Graphs: A Framework for Multi-Level Relational Data T. Koç et al. https://doi.org/10.3390/sym17122082
2229. Antimicrobial resistance trends in Escherichia coli isolated from diseased food‐producing animals in France: A 14‐year period time‐series study C. Boireau et al. https://doi.org/10.1111/zph.12412
2230. Demographic Factors Affecting Fuzzy Grading: A Hierarchical Linear Regression Analysis D. Doz et al. https://doi.org/10.3390/math11061488
2231. ChainImputer: A Neural Network-Based Iterative Imputation Method Using Cumulative Features W. Seo et al. https://doi.org/10.3390/sym17060869
2232. Soft-computing techniques for prediction of soils consolidation coefficient M. Nguyen et al. https://doi.org/10.1016/j.catena.2020.104802
2233. Accuracy of an Ultra-Wideband-Based Tracking System for Time–Motion Analysis in Tennis W. Yang et al. https://doi.org/10.3390/s25041031
2234. Adversarial Learning for Coordinate Regression Through k-Layer Penetrating Representation M. Jiang et al. https://doi.org/10.1109/TDSC.2024.3376437
2235. Analytical approaches for studying the stability of laminated roof strata M. Shabanimashcool & C. Li https://doi.org/10.1016/j.ijrmms.2015.06.007
2236. Machine Learning Analysis of Effect of Aggregate Properties on Drying Shrinkage in Concrete Y. OKAZAKI et al. https://doi.org/10.3151/crt.34.37
2237. Applying Machine Learning to Estimate the Effort and Duration of Individual Tasks in Software Projects A. Sousa et al. https://doi.org/10.1109/ACCESS.2023.3307310
2238. Modified-BRISQUE as no reference image quality assessment for structural MR images L. Chow & H. Rajagopal https://doi.org/10.1016/j.mri.2017.07.016
2239. A robust model structure selection method for small sample size and multiple datasets problems Y. Gu & H. Wei https://doi.org/10.1016/j.ins.2018.04.007
2240. Research on the Modality Transfer Method of Brain Imaging Based on Generative Adversarial Network D. Cheng et al. https://doi.org/10.3389/fnins.2021.655019
2241. Sensitivity and optimization analysis of pillar arrangement on the thermal–hydraulic performance of vapor chamber S. Zhu & Y. Li https://doi.org/10.1016/j.applthermaleng.2023.122246
2242. Predicting Soil Quality Index with a Deep Regression Approach Ş. Işık et al. https://doi.org/10.1080/00103624.2024.2305838
2243. Maize [Zea Mays (L.)] crop-nutrient response functions extrapolation for Sub-Saharan Africa G. Tesfahunegn & C. Wortmann https://doi.org/10.1007/s10705-017-9887-1
2244. Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption — A systematic review M. Khalil et al. https://doi.org/10.1016/j.engappai.2022.105287
2245. A Sequential Ensemble Model for Communicable Disease Forecasting N. Sultana et al. https://doi.org/10.2174/1574893614666191202153824
2246. Impacts of irrigated agricultural land expansion on groundwater security in Mithapukur Upazila, Bangladesh M. Monir & S. Akhter https://doi.org/10.63697/jeshs.2026.10070
2247. Artificial Vector Calibration Method for Differencing Magnetic Gradient Tensor Systems Q. Li et al. https://doi.org/10.3390/s18020361
2248. A 100 m population grid in the CONUS by disaggregating census data with open-source Microsoft building footprints X. Huang et al. https://doi.org/10.1080/20964471.2020.1776200
2249. Natural Language Processing in the Nuclear Industry: Opportunities and Challenges Y. Fayyaz et al. https://doi.org/10.1080/00295450.2025.2481358
2250. Back-Propagation Neural Network Optimized by K-Fold Cross-Validation for Prediction of Torsional Strength of Reinforced Concrete Beam Z. Lyu et al. https://doi.org/10.3390/ma15041477
2251. IoT Data Imputation Accuracy Enhancement: A Spatiotemporal Causal Mamba-Diffusion Imputation Model X. Tian et al. https://doi.org/10.1109/JIOT.2025.3590470
2252. A Mixture-of-Gaussians model for estimating the magic barrier of the recommender system H. Zhang et al. https://doi.org/10.1016/j.asoc.2021.108162
2253. Eye fatigue estimation using blink detection based on Eye Aspect Ratio Mapping(EARM) A. Kuwahara et al. https://doi.org/10.1016/j.cogr.2022.01.003
2254. Runout of rainfall-induced landslides in Malaysia K. Sim et al. https://doi.org/10.1007/s10669-025-10036-z
2255. Quantitative Analysis of Relationship Between Hypokinetic Dysarthria and the Freezing of Gait in Parkinson’s Disease J. Mekyska et al. https://doi.org/10.1007/s12559-018-9575-8
2256. Research on Effectiveness Evaluation Method of Vehicle Speed Prediction in Predictive Energy Management C. Sun et al. https://doi.org/10.3390/en19020325
2257. Optimising the computerised adaptive test to reliably reduce the burden of administering the CLEFT-Q: A Monte Carlo simulation study C. Harrison et al. https://doi.org/10.1016/j.bjps.2020.12.029
2258. A novel vehicle-bridge interaction framework for long-span bridges considering multi-scale heterogeneous traffic pattern Z. Huang et al. https://doi.org/10.1016/j.aei.2025.103871
2259. Novel Online Network Intrusion Detection System for Industrial IoT Based on OI-SVDD and AS-ELM E. Gyamfi & A. Jurcut https://doi.org/10.1109/JIOT.2022.3172393
2260. Potential Impact of Future Climates on Rice Production in Ecuador Determined Using Kobayashi’s ‘Very Simple Model’ D. Portalanza et al. https://doi.org/10.3390/agriculture12111828
2261. Enhancing Wind Power Forecasting in the Spanish Market Through Transformer Neural Networks and Temporal Optimization T. Oriol et al. https://doi.org/10.3390/su17198655
2262. Chemical recycling of polyethylene terephthalate (PET) to monomers: Mathematical modeling of the transesterification reaction of bis(2-hydroxyethyl) terephthalate to dimethyl terephthalate L. Brivio et al. https://doi.org/10.1016/j.ces.2023.119466
2263. Research on Multistate Variable Prediction of a Master‐Slave Electric‐Hydraulic Hybrid Vehicle Based on CNN‐LSTM Model with Attention Mechanism H. Chen et al. https://doi.org/10.1002/ente.202300919
2264. SCGAN-enhanced surrogate modeling for FEM analysis of induction motors: A practical use case U. Salaberria-Flaño et al. https://doi.org/10.1016/j.rineng.2025.106061
2265. Identification and 3D reconstruction of semi-rigid base loose distress from GPR B-scan using Generative Adversarial Network B. Zhang et al. https://doi.org/10.1016/j.conbuildmat.2024.139081
2266. C3DGS: Compressing 3D Gaussian Model for Surface Reconstruction of Large-Scale Scenes Based on Multiview UAV Images J. Qian et al. https://doi.org/10.1109/JSTARS.2025.3529261
2267. DFT calculations of metal-organic I-III-VI semiconductor clusters: Benchmark of exchange-correlation functionals and localized basis sets A. Olejniczak et al. https://doi.org/10.1016/j.commatsci.2019.03.036
2268. Prediction of surface roughness in duplex stainless steel face milling using artificial neural network G. Vasconcelos et al. https://doi.org/10.1007/s00170-024-13955-4
2269. Explainable multi-sensor geospatial modeling of forest biomass dynamics under compound climate extremes in subtropical monsoon regions B. Xu et al. https://doi.org/10.1080/15481603.2026.2658313
2270. Assessment and Calibration of ERA5 Severe Winds in the Atlantic Ocean Using Satellite Data R. Campos et al. https://doi.org/10.3390/rs14194918
2271. Structure–Chemistry–Tribology Coupling and Artificial-Intelligence-Assisted Performance Prediction of Cubic Boron Nitride-Reinforced Heat-Polymerized PMMA Denture Base Composites A. Sincar et al. https://doi.org/10.3390/cryst16090550
2272. How accurate are estimates of flower visitation rates by pollinators? Lessons from a spatially explicit agent-based model M. Santos et al. https://doi.org/10.1016/j.ecoinf.2020.101077
2273. Long-Term Traffic Flow Prediction for Highways Based on STLLformer Model Y. Shen et al. https://doi.org/10.3390/su172210078
2274. Assessing the Impact of Spatial Resolution and Aggregation Method on Sentinel-2 NDVI Time Series in Grasslands of Mainland Spain T. Pugni-Stanek et al. https://doi.org/10.3390/rs18152611
2275. Inductive reasoning for significant concept and pattern discovery in cognitive IoT V. Jha & P. Tripathi https://doi.org/10.1007/s11761-024-00416-9
2276. Optical design and coating optimization of the Wolter-I X-ray telescope Y. Geng et al. https://doi.org/10.1364/AO.533818
2277. Drivers and threshold responses of surface structural vulnerability in the hilly dryland of southern China Y. Cai et al. https://doi.org/10.1016/j.jenvman.2026.130347
2278. Rainfall estimation methods in the Brazilian semiarid region: 30‐year evaluation on a monthly scale V. dos Santos et al. https://doi.org/10.1002/joc.6723
2279. A Two-Parameter Model for Water-Lubricated Pipeline Transportation of Unconventional Crudes S. Rushd et al. https://doi.org/10.3390/en14185665
2280. Rock Strain Prediction Using Deep Neural Network and Hybrid Models of ANFIS and Meta-Heuristic Optimization Algorithms T. Pradeep et al. https://doi.org/10.3390/infrastructures6090129
2281. Deep learning mechanism and big data in hospitality and tourism: Developing personalized restaurant recommendation model to customer decision-making S. Yang et al. https://doi.org/10.1016/j.ijhm.2024.103803
2282. A review of the top of the barrier nanotransistor models for semiconductor nanomaterials M. Chuan et al. https://doi.org/10.1016/j.spmi.2020.106429
2283. Nested Cross-Validation for HBV Conceptual Rainfall–Runoff Model Spatial Stability Analysis in a Semi-Arid Context M. El Garnaoui et al. https://doi.org/10.3390/rs16203756
2284. Transformer-Based hyperspectral image analysis for phenotyping drought tolerance in blueberries M. Rahman et al. https://doi.org/10.1016/j.compag.2024.109684
2285. Bernstein polynomials and Bezier curves: a novel modeling approach to secure ECG data transmission P. Rajagopal et al. https://doi.org/10.1007/s41870-023-01629-5
2286. Predicting exposure concentrations of chemicals with a wide range of volatility and hydrophobicity in different multi-well plate set-ups J. Stadnicka-Michalak et al. https://doi.org/10.1038/s41598-021-84109-9
2287. Draw Curves of the Rainfall Intensity-Duration-Frequency by Using Multilayer Artificial Neural Network for Al-Najaf Al-Ashraf A. Hussein et al. https://doi.org/10.67635/pjeas.2020.26.1.302
2288. Fuzzy midpoint–based imputation methods for non-parametric survival estimation with interval-censored data K. Manungo et al. https://doi.org/10.3389/fams.2026.1836441
2289. Predicting unparalleled degradation progression in PV module using simulation of shunt resistance experimental data H. Mahdi https://doi.org/10.1016/j.egyr.2024.09.012
2290. Applications of machine learning algorithms and neural networks in slope stability analysis: a review and outlook D. Li et al. https://doi.org/10.1007/s12517-025-12375-2
2291. Data-driven analysis of CO2 loading behavior in aqueous diisopropanolamine-based amine blends M. Dehbani et al. https://doi.org/10.1016/j.dche.2026.100338
2292. Predictive modeling of combined cycle power plant performance using a digital twin-based neural ODE approach A. Wan et al. https://doi.org/10.1016/j.jobe.2024.110390
2293. Predicting hydrogen production from formic acid dehydrogenation using smart connectionist models S. Tazikeh et al. https://doi.org/10.1016/j.ijhydene.2025.01.502
2294. A Mathematical and Computational Model for Multiple COVID-19 Waves Applied to Kenya W. Ogana et al. https://doi.org/10.4236/jamp.2025.134072
2295. QMe14S: A Comprehensive and Efficient Spectral Data Set for Small Organic Molecules M. Yuan et al. https://doi.org/10.1021/acs.jpclett.5c00839
2296. Prediction of sensory textures of cosmetics using large amplitude oscillatory shear and extensional rheology H. Lee et al. https://doi.org/10.1515/arh-2024-0016
2297. A Holistic Integration of Machine Learning for Selecting Optimum Ratio of Nanoparticles in Epoxy-Based Nanocomposite Insulators A. Siddique et al. https://doi.org/10.3390/pr13082330
2298. SVD-based adaptive fuzzy for generalized transportation M. Aljanabi et al. https://doi.org/10.1016/j.aej.2024.03.020
2299. Prediction of Polish Holstein's economical index and calving interval using machine learning J. Wełeszczuk et al. https://doi.org/10.1016/j.livsci.2022.105039
2300. Machine Learning–Driven Bioprospecting of Cholinergic Medicinal Plants for Putative Leads Against Butyrylcholinesterase Towards Alzheimer’s Care G. Gyebi et al. https://doi.org/10.1155/bri/4503245
2301. Data-Driven Approaches for Vibroacoustic Localization of Leaks in Water Distribution Networks R. Liu et al. https://doi.org/10.1007/s40710-024-00682-x
2302. Determination of the composition of heterogeneous binder solutions by surface plasmon resonance biosensing J. Gaudreault et al. https://doi.org/10.1038/s41598-021-83268-z
2303. FDST-GCN: A Fundamental Diagram based Spatiotemporal Graph Convolutional Network for expressway traffic forecasting J. Zhang et al. https://doi.org/10.1016/j.physa.2023.129173
2304. Monitoring ryegrass-clover grasslands with multi-spectral UAV imagery will improve the sustainability of small-and medium-sized livestock farmers in the northern Peruvian highlands L. Vallejos-Fernández et al. https://doi.org/10.1080/27658511.2026.2623335
2305. Mobility aware autonomic approach for the migration of application modules in fog computing environment J. Martin et al. https://doi.org/10.1007/s12652-020-01854-x
2306. Simulation of the Hydrodynamic Functioning of the Cavally River Using a Coupled 1D-2D Model in the Ity Area (Zouan-Hounien in C&#244;te d’Ivoire) A. Yao et al. https://doi.org/10.4236/ojmh.2021.114005
2307. Influence of climate variability and land cover dynamics on the spatio-temporal NDVI patterns in western hydrological regions of Bangladesh J. Akhter & R. Afroz https://doi.org/10.1016/j.heliyon.2024.e32625
2308. Development of High Resolution Cloud Cover Climatology Databank Using Merged Manual and Satellite Datasets over Ghana, West Africa P. Asilevi Junior et al. https://doi.org/10.1080/07055900.2022.2072266
2309. Preparation of multifunctional hydrogels based on co-pigment-polysaccharide complexes and establishment of a machine learning monitoring platform F. Cui et al. https://doi.org/10.1016/j.ijbiomac.2024.129258
2310. Proposal of Bot Detection Method by Multi-Source Access Log Analysis T. Tanaka & K. Tsuda https://doi.org/10.1541/ieejeiss.141.1205
2311. Review of medical image quality assessment L. Chow & R. Paramesran https://doi.org/10.1016/j.bspc.2016.02.006
2312. A new infiltration model for simulating soil water movement in canal irrigation under laboratory conditions Q. Fu et al. https://doi.org/10.1016/j.agwat.2018.10.021
2313. Acoustic sampling of Antarctic krill with simulated underwater buoyancy gliders: Does the sawtooth dive pattern work? D. Kinzey et al. https://doi.org/10.3389/fmars.2022.1064181
2314. A method on modelling and analyzing the power losses in vehicle transmission Y. Shen & S. Rinderknecht https://doi.org/10.1007/s10010-018-0276-y
2315. Modeling Salmonella spp. inactivation in chicken meat subjected to isothermal and non-isothermal temperature profiles T. Milkievicz et al. https://doi.org/10.1016/j.ijfoodmicro.2021.109110
2316. Predicting Missing Values in Spatio-Temporal Remote Sensing Data F. Gerber et al. https://doi.org/10.1109/TGRS.2017.2785240
2317. LSTM Learning Enhanced Deep Cone Thickening and Paste Backfilling for High Density Tailings: A Case Study R. Guo et al. https://doi.org/10.23919/METAR.2026.000048
2318. New strength–strain model and stress–strain relationship for square and rectangular concrete columns confined with CFRP wraps N. Diboune et al. https://doi.org/10.1080/15376494.2022.2067604
2319. Using an inverse surrogate model for determining building thermal characteristics L. Jowett-Lockwood & R. Evins https://doi.org/10.1080/19401493.2025.2487459
2320. Estimation of the Concentration of XCO2 from Thermal Infrared Satellite Data Based on Ensemble Learning X. Gong et al. https://doi.org/10.3390/atmos15010118
2321. Porovnání kvality schematizace údolnice extrahované z dat DMR 4G, DMR 5G a jeho derivátů L. Bureš et al. https://doi.org/10.46555/VTEI.2024.01.001
2322. Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing B. Yan et al. https://doi.org/10.3390/w13213133
2323. A Low-Cost 3D Mapping System for Indoor Scenes Based on 2D LiDAR and Monocular Cameras X. Li et al. https://doi.org/10.3390/rs16244712
2324. Predicting the Performance of PEM Fuel Cells by Determining Dehydration or Flooding in the Cell Using Machine Learning Models J. Zaveri et al. https://doi.org/10.3390/en16196968
2325. Generating High Spatial and Temporal Surface Albedo with Multispectral-Wavemix and Temporal-Shift Heatmaps S. Karalasingham et al. https://doi.org/10.3390/rs17030461
2326. Comparative Evaluation of NARX Model Training Algorithms for PM₁₀ Forecasting in Amasya, TÜRKİYE G. Özdoğan Sarıkoç https://doi.org/10.65520/erciyesfen.1911367
2327. The effect of climate change on groundwater level and its prediction using modern meta-heuristic model R. Dehghani et al. https://doi.org/10.1016/j.gsd.2021.100702
2328. Secondary iron ion contamination of water in the water supply network M. Wojtkowska & M. Potyralla https://doi.org/10.5004/dwt.2022.28970
2329. Comparing field-scale eddy covariance measurements and crop coefficient estimates of alfalfa evapotranspiration to OpenET model estimates and exploring water budget implications in a dryland environment L. Sabiston et al. https://doi.org/10.1007/s00271-024-00941-7
2330. Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon electricity demand forecasting M. AL-Musaylh et al. https://doi.org/10.1016/j.apenergy.2018.02.140
2331. Early warning indicators for mesophilic anaerobic digestion of corn stalk: a combined experimental and simulation approach Y. Wu et al. https://doi.org/10.1186/s13068-019-1442-7
2332. Stabilization of Expansive Clays with Basalt Fibers and Prediction of Strength by Machine Learning S. Sert et al. https://doi.org/10.1007/s13369-024-08752-w
2333. A comparison of the performance of the CSM-CERES-Maize and EPIC models using maize variety trial data Y. Bao et al. https://doi.org/10.1016/j.agsy.2016.10.006
2334. Modeling the effect of temperature history on the lag phase duration of Listeria monocytogenes H. Kapoor et al. https://doi.org/10.1016/j.microb.2026.100771
2335. Expertise Detection in Crowdsourcing Forums Using the Composition of Latent Topics and Joint Syntactic–Semantic Cues Y. Woldemariam https://doi.org/10.1007/s42979-021-00832-0
2336. Explainable Machine Learning Prediction of Vehicle CO2 Emissions for Sustainable Energy and Transport D. Yuan et al. https://doi.org/10.3390/en18205408
2337. Automated morphometric modelling of an endangered freshwater cetacean from unscaled UAV imagery using an internal scaling framework H. Zhou et al. https://doi.org/10.1016/j.ecoinf.2026.104070
2338. Comparison of RBF and MLP neural network performance and regression analysis to estimate carbon sequestration F. Cheshmberah et al. https://doi.org/10.1007/s13762-020-02696-y
2339. Advancements in Mixed Reality for Autonomous Vehicle Testing and Advanced Driver Assistance Systems: A Survey I. Argui et al. https://doi.org/10.1109/TITS.2024.3473740
2340. Evaluation of Water Quality Based on a Machine Learning Algorithm and Water Quality Index for Mid Gangetic Region (South Bihar plain), India A. Gupta et al. https://doi.org/10.1007/s12594-021-1821-0
2341. Compressibility of expansive soil mixed with sand and its correlation to index properties A. Alnmr et al. https://doi.org/10.1016/j.heliyon.2024.e35711
2342. Towards Rational Design of Confined Catalysis in Carbon Nanotube by Machine Learning and Grand Canonical Monte Carlo Simulations C. Yang et al. https://doi.org/10.1002/anie.202421552
2343. The Phase Noise Transfer Model in the Phase-Generated-Carrier-Based Interferometric Fiber-Optic Sensor Y. Zhang et al. https://doi.org/10.1109/JSEN.2022.3180587
2344. Design, Modeling, and Control of a Fully Actuated Multirotor with Multidirectional Thrusts M. Ghazali et al. https://doi.org/10.1142/S2301385026500391
2345. The Role of Performance Metrics in Estimating Market Values of Footballers in Europe's Top Five Leagues M. Yalçınkaya & M. Işık https://doi.org/10.54141/psbd.1489554
2346. Generation of Loss Functions from Matrix-Based Binary Classification Metrics D. Han et al. https://doi.org/10.1145/3805705
2347. Analysis and Modeling of Statistical Distribution Characteristics for Multi-Aspect SAR Images R. Zhu et al. https://doi.org/10.3390/rs17071295
2348. Enhanced Runoff Modeling by Incorporating Information from the GR4J Hydrological Model and Multiple Remotely Sensed Precipitation Datasets C. Mo et al. https://doi.org/10.3390/w16040530
2349. A comparison of methods for the derivation of classroom ventilation rates from CO2 measurements F. Pollozhani et al. https://doi.org/10.1016/j.buildenv.2026.114288
2350. Accounting for Local Geological Variability in Sequential Simulations—Concept and Application A. Linsel et al. https://doi.org/10.3390/ijgi9060409
2351. Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases H. Ko et al. https://doi.org/10.1155/2023/9965226
2352. Adaptive Antenna Array Control Algorithm in Radiocommunication Systems M. Wnuk https://doi.org/10.3390/a17020081
2353. Electrical Energy Demand Forecasting Model Development and Evaluation with Maximum Overlap Discrete Wavelet Transform-Online Sequential Extreme Learning Machines Algorithms M. Al-Musaylh et al. https://doi.org/10.3390/en13092307
2354. Toward Improving the Efficiency of Software Development Effort Estimation via Clustering Analysis V. Van Hai et al. https://doi.org/10.1109/ACCESS.2022.3185393
2355. Climate change and crop yields in Zambia: historical effects and future projections K. Mulungu et al. https://doi.org/10.1007/s10668-020-01146-6
2356. CFPNet-M: A light-weight encoder-decoder based network for multimodal biomedical image real-time segmentation A. Lou et al. https://doi.org/10.1016/j.compbiomed.2023.106579
2357. Downdrift Port Siltation Adjacent to a River Mouth: Mechanisms and Effects of Littoral Sediment Transport to the Navigation Channel A. Romdani et al. https://doi.org/10.1061/(ASCE)WW.1943-5460.0000700
2358. Prediction of the spatial distribution of soil organic carbon content in Central European agriculturally used peatlands: a case study of the Grójec Valley, Central Poland S. Pindral et al. https://doi.org/10.1007/s11368-026-04271-3
2359. Fire Resistance Prediction in FRP-Strengthened Structural Elements: Application of Advanced Modeling and Data Augmentation Techniques Ü. Işıkdağ et al. https://doi.org/10.3390/pr13103053
2360. Gridded precipitation and temperature products performance over Afghanistan: from simple bias correction to advanced data fusion M. Nasimi et al. https://doi.org/10.1080/01431161.2025.2600097
2361. A machine learning-based framework toward predicting PFAS degradation and defluorination in electrochemical oxidation with automated EE/O estimation H. Kim et al. https://doi.org/10.1016/j.desal.2026.120788
2362. Calibration of microwave antenna for porous materials moisture evaluation using frequency domain analysis K. Tabiś et al. https://doi.org/10.1088/1742-6596/2628/1/012030
2363. An materials informatics approach to Ni-based single crystal superalloys lattice misfit prediction X. Jiang et al. https://doi.org/10.1016/j.commatsci.2017.09.061
2364. Surface Roughness Prediction of AISI 304 Steel in Nanofluid Assisted Turning Using Machine Learning Technique P. Prasad et al. https://doi.org/10.4028/p-wwb643
2365. Machine learning–assisted prediction of heat fluxes through thermally anisotropic building envelopes Z. Shen et al. https://doi.org/10.1016/j.buildenv.2023.110157
2366. A novel approach to predict green density by high-velocity compaction based on the materials informatics method K. Zhang et al. https://doi.org/10.1007/s12613-019-1724-x
2367. Capturing Curved Lag Plots in Dye Adsorption Kinetics Using a Generalized Three-State Discrete-Time Markov Chain Model D. Lei & J. Huang https://doi.org/10.1007/s12221-025-01302-7
2368. Monitoring, Diffusion and Source Speculation Model of Urban Soil Pollution Z. Li et al. https://doi.org/10.3390/pr8111339
2369. Advanced Machine Learning and Gene Expression Programming Techniques for Predicting CO₂-Induced Alterations in Coal Strength Z. Liu et al. https://doi.org/10.32604/cmes.2025.062426
2370. INITIAL APPLICATION OF NONLINEAR REGRESSION MODELS TO ASSESS BIOLOGICAL SELF-PURIFICATION CAPACITY IN VUNG RO BAY (PHU YEN) N. Huan & N. Hieu https://doi.org/10.15625/1859-3097/18/4A/13641
2371. Spurring sustainability commitment strategy of family-owned SMEs: A multi-analytical SEM & ANFIS perspective K. Khaw et al. https://doi.org/10.1016/j.hitech.2023.100453
2372. Development of a System for Predicting Photovoltaic Power Generation and Detecting Defects Using Machine Learning S. Lee & W. Lee https://doi.org/10.3745/KTCCS.2016.5.10.353
2373. Machine learning approaches for enhanced estimation of reference evapotranspiration (ETo): a comparative evaluation A. Farag https://doi.org/10.1038/s41598-025-23166-w
2374. Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non‐invasive hyperspectral imaging technique R. Md Saleh et al. https://doi.org/10.1111/jfpp.16460
2375. Calibration and validation of the AquaCrop model for simulating cotton growth under a semi-arid climate in Uzbekistan J. Boulange et al. https://doi.org/10.1016/j.agwat.2025.109360
2376. MapGen-Diff: An End-to-End Remote Sensing Image to Map Generator via Denoising Diffusion Bridge Model J. Tian et al. https://doi.org/10.3390/rs16193716
2377. The Capabilities of WRF in Simulating Extreme Rainfall over the Mahalapye District of Botswana K. Monaka et al. https://doi.org/10.3390/atmos17020135
2378. Parallel Princeton Ocean Model based on OpenACC Y. Wang et al. https://doi.org/10.1016/j.envsoft.2025.106370
2379. Modeling daily reference evapotranspiration via a novel approach based on support vector regression coupled with whale optimization algorithm B. Mohammadi & S. Mehdizadeh https://doi.org/10.1016/j.agwat.2020.106145
2380. Analyzing the ENVI-met microclimate model’s performance and assessing cool materials and urban vegetation applications–A review S. Tsoka et al. https://doi.org/10.1016/j.scs.2018.08.009
2381. Real option valuation using Weibull distribution: a new framework for depreciation risk management S. Ko https://doi.org/10.1108/JDQS-10-2024-0041
2382. Load prediction for high-speed train bogie frames under multiple speed conditions using a hybrid 1DCNN-LSTM model Y. Chen et al. https://doi.org/10.1016/j.ijfatigue.2026.109790
2383. Machine learning technology for early prediction of grain yield at the field scale: A systematic review J. Leukel et al. https://doi.org/10.1016/j.compag.2023.107721
2384. Discrete-Time Markov Chain-Based Adsorption Kinetic Model for Textile Exhaust Dyeing D. Lei & J. Huang https://doi.org/10.1007/s12221-025-01010-2
2385. Intercomparison of tropical Indian Ocean circulation in ocean reanalysis and evaluation in CMIP6 climate models P. Bhanu Deepika et al. https://doi.org/10.1016/j.dynatmoce.2024.101456
2386. Evolutionary Framework with Bidirectional Long Short-Term Memory Network for Stock Price Prediction H. Zheng et al. https://doi.org/10.1155/2021/8850600
2387. Recent Advances in Deep Learning-Based Toxicity Prediction of Emerging Organic Pollutants in Freshwater Ecosystems T. Kankpiabe et al. https://doi.org/10.1007/s40726-026-00401-0
2388. Ultrasonic testing on evaluation of concrete residual compressive strength: A review M. Moura et al. https://doi.org/10.1016/j.conbuildmat.2023.130887
2389. Multi-source remote sensing of tropical montane forest structure for degradation risk and restoration prioritization S. Khankeshizadeh et al. https://doi.org/10.1016/j.srs.2026.100481
2390. HIPACO: An RSSI Indoor Positioning Algorithm Based on Improved Ant Colony Optimization Algorithm Y. Zhao & B. Jin https://doi.org/10.3390/a18100654
2391. Machine learning models for predicting physical properties in asphalt road construction: A systematic review J. Leukel et al. https://doi.org/10.1016/j.conbuildmat.2024.137397
2392. Predicting single-cell protein production from food-processing wastewater in sequencing batch reactors using ensemble learning R. Huang et al. https://doi.org/10.1016/j.biortech.2025.132561
2393. Analytical study of multi-layer one-dimensional spatially dependent solute transport modeling P. Bharti et al. https://doi.org/10.1007/s10652-025-10058-w
2394. A Study on Data Acquisition for a Centrifugal Pump using a CFD-based Digital Twin Simulation Model H. Park et al. https://doi.org/10.14801/jkiit.2026.24.4.19
2395. Systematic analysis of nuclear binding energy using XGBoost residual modeling M. Hassani et al. https://doi.org/10.1515/zna-2026-0074
2396. Assessing spatial predictive models in the environmental sciences: Accuracy measures, data variation and variance explained J. Li https://doi.org/10.1016/j.envsoft.2016.02.004
2397. A Spatiotemporal Flight Trajectory Prediction and Online Learning Framework Based on Integrated Transformer-Bidirectional Gated Recurrent Unit Y. Liu et al. https://doi.org/10.1109/TITS.2025.3614658
2398. Electrical resistivity tomography for characterization of carbon-rich rocks (shungites) P. Ryazantsev & Y. Deines https://doi.org/10.1016/j.jappgeo.2022.104667
2399. Machine learning-driven mapping of prokaryotic community diversity in the Mediterranean Sea using omics, earth observation, and model data C. Marchese et al. https://doi.org/10.1016/j.ecoinf.2026.103747
2400. Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data A. Ahmed et al. https://doi.org/10.3390/rs13040554
2401. MODWT-ANN hybrid models for daily precipitation estimates with time-delayed entries in Amazon region E. Gomes et al. https://doi.org/10.1007/s10661-022-09939-0
2402. Deep Learning Estimation of Daily Ground‐Level NO2 Concentrations From Remote Sensing Data M. Ghahremanloo et al. https://doi.org/10.1029/2021JD034925
2403. GAT-EGRU: A Deep Learning Prediction Model for PM2.5 Coupled with Empirical Modal Decomposition Algorithm G. Yang et al. https://doi.org/10.1007/s11518-023-5562-z
2404. Evaluation of ALOS-2/PALSAR-2 L-Band SAR Polarimetric Parameters for Water-Level Estimation in Irrigated Rice Paddy Fields D. Novresiandi et al. https://doi.org/10.3390/rs18091313
2405. Synthesized CaO-Based Nanocatalysts for Sustainable Biodiesel Production: Artificial Intelligence (AI) Optimization of a Green Nanotechnological Strategy toward Reactor Design M. BenSlimene & T. Saleh https://doi.org/10.1021/acssuschemeng.5c12234
2406. Sensitivity and optimization analysis of thermal-hydraulic performance of a metal foam coated airfoil tube crossflow heat exchanger Z. Haokun et al. https://doi.org/10.1016/j.applthermaleng.2025.127140
2407. Towards resilient water management in deltaic Bangladesh: benchmarking an exogenous regressor-enhanced prophet framework for multi-Lag river stage forecasting M. Islam et al. https://doi.org/10.2166/wp.2026.064
2408. Prediction model of PTO shaft fatigue damage considering sandy loam and loam in rotary-tillage operation M. Jang et al. https://doi.org/10.4081/jae.2025.1610
2409. Kilometre-Scale Climate Projections for Nicosia: Dynamical and Machine Learning Downscaling to Detect Future Intra-Urban Heat Hotspots K. Koutroumanou-Kontosi et al. https://doi.org/10.3390/cli14070152
2410. Evaluation of empirical and mechanistic models and sampling intervals to model the lactation curves of F1 dairy sheep L. Guevara et al. https://doi.org/10.1007/s11250-025-04365-z
2411. Using bootstrap ELM and LSSVM models to estimate river ice thickness in the Mackenzie River Basin in the Northwest Territories, Canada R. Barzegar et al. https://doi.org/10.1016/j.jhydrol.2019.06.075
2412. Modeling and scenario-based risk estimation of Listeria monocytogenes in meatballs and Sundae, a Korean black pudding, under different packaging conditions J. Park & H. Kim https://doi.org/10.1016/j.foodcont.2023.109886
2413. Using Artificial Intelligence-Based Machine Learning Regression Models for Predictions of Home Prices M. Tyagadurgam et al. https://doi.org/10.59324/ejaset.2025.3(3).29
2414. Textual variations affect human judgements of sentiment values P. Teh et al. https://doi.org/10.1016/j.elerap.2022.101149
2415. Utilizing GaoFen-2 derived urban green space information to predict local surface temperature D. Chen et al. https://doi.org/10.1016/j.ufug.2024.128463
2416. Yield Curve Modeling: Applicability of the Traditional Factor Models for Sri Lanka Government Bonds K. Dayarathne & U. Thayasivam https://doi.org/10.1007/s42979-025-04075-1
2417. Navigating yield-density trade-offs in maize production: A Bayesian-ML framework for uncertainty attribution and management R. Lei et al. https://doi.org/10.1016/j.fcr.2026.110480
2418. Decoupling between heat loss indicators and heating demand in a high-mass dwelling: implications for interpreting building performance G. Harvey & S. Szentesi-Nejur https://doi.org/10.3389/fbuil.2026.1881793
2419. Comparing COSMO-CLM simulations and MODIS data of snow cover extent and distribution over Italian Alps P. Da Ronco et al. https://doi.org/10.1007/s00382-016-3054-2
2420. Pool-mamba: Pooling state space model for low-light image enhancement Q. Zhang et al. https://doi.org/10.1016/j.neucom.2025.130005
2421. Applying sustainable development goals in financial forecasting using machine learning techniques A. Chang et al. https://doi.org/10.1002/csr.2694
2422. Benchmark of Electricity Consumption Forecasting Methodologies Applied to Industrial Kitchens J. Amantegui et al. https://doi.org/10.3390/buildings12122231
2423. Substrate moisture variations of extensive green roofs with different structural configurations in a semi-arid region: Observational data and dynamic simulation W. Liu et al. https://doi.org/10.1016/j.jhydrol.2023.130133
2424. An Efficient Approach for Missing Data Recovery in Cognitive IoT Sensor Network V. Jha & P. Tripathi https://doi.org/10.1007/s43069-025-00546-6
2425. Active layer modelling at Stelvio Pass, Italian Alps V. Chaturvedi et al. https://doi.org/10.1016/j.coldregions.2025.104762
2426. Exploring University Ranking Stability and Predictability: Cross-Ranking Consistency, Persistence Baselines, and Machine Learning E. Andekin et al. https://doi.org/10.3390/analytics5040040
2427. Optimization algorithms as training approach with hybrid deep learning methods to develop an ultraviolet index forecasting model A. Ahmed et al. https://doi.org/10.1007/s00477-022-02177-3
2428. Prediction of battery thermal behaviour in the presence of a constructal theory-based heat pipe (CBHP): A multiphysics model and pattern-based machine learning approach K. Boonma et al. https://doi.org/10.1016/j.est.2022.103963
2429. From Eye Movements to Personality Traits: A Machine Learning Approach in Blood Donation Advertising S. Balaskas et al. https://doi.org/10.3390/ai5020034
2430. Generating high-resolution daily soil moisture by using spatial downscaling techniques: a comparison of six machine learning algorithms Y. Liu et al. https://doi.org/10.1016/j.advwatres.2020.103601
2431. Evaluation of using the time-dependent density functional theory in studying the fluorescence properties of coumarin derivatives N. Hien et al. https://doi.org/10.1039/D3NJ05220F
2432. Study on Autoencoder-based Plant Piping Leak Detection S. Park et al. https://doi.org/10.14801/jkiit.2023.21.11.1
2433. Continuous Assessment of Function and Disability via Mobile Sensing: Real-World Data-Driven Feasibility Study E. Sükei et al. https://doi.org/10.2196/47167
2434. Ground-Tunnel Frequency-domain Electromagnetic Detection of Deeply-buried Metal Deposit: A Practice under Complex Production Noise H. Wang et al. https://doi.org/10.1007/s11770-026-1525-8
2435. Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time S. Ayvaz & K. Alpay https://doi.org/10.1016/j.eswa.2021.114598
2436. A Statistical Approach on Estimations of Climate Change Indices by Monthly Instead of Daily Data K. Hasel et al. https://doi.org/10.3390/atmos14111634
2437. PIN: A new metric to evaluate solar irradiance forecast models A. Temporal-Neto et al. https://doi.org/10.1016/j.egyr.2025.01.076
2438. Materials process informatics-assisted precise particle size control of metal–organic frameworks Y. Wang et al. https://doi.org/10.1039/D6SC03212E
2439. Nanozyme-based colorimetric sensor arrays coupling with smartphone for discrimination and “segmentation-extraction-regression” deep learning assisted quantification of flavonoids Y. Qin et al. https://doi.org/10.1016/j.bios.2024.116604
2440. Multi-objective optimization of petroleum engineering problems using a hybrid workflow: Combination of particle swarm optimization, fuzzy logic, imperialist competitive algorithm and response surface methodology M. Karambeigi et al. https://doi.org/10.1016/j.geoen.2023.211579
2441. Perceptive Self-Supervised Learning Network for Noisy Image Watermark Removal C. Tian et al. https://doi.org/10.1109/TCSVT.2024.3349678
2442. Optimizing compressive strength prediction of pervious concrete using artificial neural network S. Wijekoon et al. https://doi.org/10.1088/2631-8695/adb129
2443. Epistemic and aleatoric uncertainty in optical vegetation trait retrieval: Concepts, Methods, and Outlook J. Verrelst et al. https://doi.org/10.1016/j.isprsjprs.2026.02.020
2444. Estimating Maximum Daily Precipitation in the Upper Vistula Basin, Poland D. Młyński et al. https://doi.org/10.3390/atmos10020043
2445. Structural monitoring data repair based on a long short-term memory neural network B. Panfeng et al. https://doi.org/10.1038/s41598-024-60196-2
2446. Desempenho de Métodos de Preenchimento de Falhas em Dados de Evapotranspiração de Referência para Região Oeste do Paraná T. Giovanella et al. https://doi.org/10.1590/0102-77863630001
2447. Modeling Electromagnetic Navigation Systems S. Charreyron et al. https://doi.org/10.1109/TRO.2020.3047053
2448. Developing a More Reliable Framework for Extracting Traffic Data From a UAV Video X. Li & J. Wu https://doi.org/10.1109/TITS.2023.3290827
2449. Satellite‐based regional‐scale evapotranspiration estimation mapping of the rice bowl of Tamil Nadu: A little water to spare* M. Hari et al. https://doi.org/10.1002/ird.2553
2450. Predicting the experimental data of the substrate specificity of Aspergillus niger inulinase using mathematical models, estimating kinetic constants in the Michaelis–Menten equation, and sensitivity analysis M. Germec & I. Turhan https://doi.org/10.1007/s13399-021-01830-1
2451. Predictive Utility of In-Hospital Screening for Postdischarge Depression Symptoms Among Survivors of Critical Illness I. Shubert et al. https://doi.org/10.1016/j.chstcc.2026.100279
2452. Morphodynamic processes evolution and structural impact assessment of the Karnafuli River M. Nujhat et al. https://doi.org/10.1007/s40808-025-02328-9
2453. Copula-based joint distribution modelling of precipitation, temperature and humidity events in the assessments of agricultural risks, with a case study in Morocco S. Latif et al. https://doi.org/10.1007/s00477-025-03047-4
2454. In silico aquatic toxicity prediction of chemicals toward Daphnia magna and fathead minnow using Monte Carlo approaches S. Lotfi et al. https://doi.org/10.1080/15376516.2024.2416226
2455. Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand N. Thanh et al. https://doi.org/10.1016/j.envres.2024.118952
2456. Vascular-related biological stress, DNA methylation, allostatic load and domain-specific cognition: an integrated machine learning and causal inference approach R. Waziry et al. https://doi.org/10.1186/s12883-025-04185-6
2457. Integrasi ESP32 dan Multi-Soil Sensor RS485 dalam Monitoring Parameter Tanah Real-Time M. Sri Muna et al. https://doi.org/10.29303/jrpb.v14i2.1241
2458. A parallel methodology using radial basis functions versus machine learning approaches applied to environmental modelling V. Migallón et al. https://doi.org/10.1016/j.jocs.2022.101817
2459. CGP-Uformer: A low-dose CT image denoising Uformer based on channel graph perception H. Yan et al. https://doi.org/10.3233/XST-230158
2460. Evaluating performances of SVR, HBA–SVR, and COOT–SVR techniques: monthly evaporation modeling in Algeria M. Achite et al. https://doi.org/10.1007/s41207-025-00916-w
2461. A review of model evaluation metrics for machine learning in genetics and genomics C. Miller et al. https://doi.org/10.3389/fbinf.2024.1457619
2462. Aerodynamic Performance and Wake Validation of Micro Wind Turbines Using CFD and SPIV S. Zhang et al. https://doi.org/10.1088/1742-6596/3016/1/012032
2463. Process simulation of hydrogen production through biomass gasification: Introduction of torrefaction pre-treatment Y. Yong & R. Abdul Rasid https://doi.org/10.1016/j.ijhydene.2021.07.010
2464. Sensitivity analysis of observational nudging methodology to reduce error in wind resource assessment (WRA) in the North Sea M. Mylonas et al. https://doi.org/10.1016/j.renene.2017.12.088
2465. Impedance measurement of lithium-ion batteries using optimized pulse patterns L. Lignell et al. https://doi.org/10.1016/j.est.2025.118590
2466. How fast does tufa grow? Very high‐resolution measurement of the tufa growth rate on artificial substrates by the development of a contactless image‐based modelling device I. Marić et al. https://doi.org/10.1002/esp.4883
2467. Lesson (un)replicated: Predicting levels of political violence in Afghan administrative units per month using ARFIMA and ICEWS data T. Libel https://doi.org/10.1017/dap.2022.26
2468. Development and Validation of an Openable Spherical Target System for High-Precision Registration and Georeferencing of Terrestrial Laser Scanning Point Clouds M. Makuch & P. Gawronek https://doi.org/10.3390/s25247512
2469. Robust Model Predictive Control-Based Recurrent Neural Networks for Autonomous Vehicles in Avoidance Collisions H. Duy Nguyen et al. https://doi.org/10.1109/ACCESS.2025.3579216
2470. Distribution of phytoplankton using remote sensing in Cimandiri Estuary, Sukabumi, West Java F. Firdaus et al. https://doi.org/10.1088/1755-1315/481/1/012066
2471. Utilizing Artificial Intelligence to Predict the Superplasticizer Demand of Self-Consolidating Concrete Incorporating Pumice, Slag, and Fly Ash Powders J. Liu et al. https://doi.org/10.3390/ma14226792
2472. Comparing Single and Multiple Imputation Approaches for Missing Values in Univariate and Multivariate Water Level Data N. Umar & A. Gray https://doi.org/10.3390/w15081519
2473. Forecasting Liquefied Natural Gas Bunker Prices Using Artificial Neural Network for Procurement Management K. Kim et al. https://doi.org/10.3390/jmse10121814
2474. A new multivariate blood glucose prediction method with hybrid feature clustering and online transfer learning F. You et al. https://doi.org/10.1007/s13755-024-00313-7
2475. Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model C. Zhang & M. Yang https://doi.org/10.3390/app15073530
2476. Experimental validation of an IoT-integrated maturity and machine learning method for concrete strength prediction U. Upadhyay et al. https://doi.org/10.1007/s42452-026-08769-w
2477. Assessment of Climatic Parameters for Future Climate Change in a Major Agricultural State in India R. Jha et al. https://doi.org/10.3390/cli9070111
2478. Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour-Change Project R. West et al. https://doi.org/10.12688/wellcomeopenres.20000.1
2479. Machine Learning-Driven Strength Prediction and Sustainability Analysis of Ultra-High-Performance Concrete H. Rong et al. https://doi.org/10.3390/ma18225116
2480. A Validation of Temporal Downscaling Models of Estimating Hourly Temperatures Under South African Conditions P. Tharaga et al. https://doi.org/10.3390/atmos17070637
2481. Reliability and Validity Analysis of Correlations on Strength and Consolidation Parameters for Ankara Clay and Proposal for a New Correlation E. Tuc et al. https://doi.org/10.1007/s13369-024-09181-5
2482. Data-driven modeling of Galactic diffuse emission with multi-wavelength observations X. Liu et al. https://doi.org/10.1140/epjc/s10052-026-16408-2
2483. Imprecise reasoning: extracting precision in imprecision for knowledge discovery in cognitive IoT V. Jha & P. Tripathi https://doi.org/10.1007/s42044-025-00236-w
2484. Development of bubble point pressure and oil formation volume factor models using pressure-volume-temperature data G. Mwakipunda et al. https://doi.org/10.1016/j.jrmge.2025.02.027
2485. An AI-based algorithm for retrieving aerosol optical depth and single scattering albedo using All-Sky Imager observations H. Ni et al. https://doi.org/10.5194/amt-19-5871-2026
2486. Ensemble Machine-Learning-Based Prediction Models for the Compressive Strength of Recycled Powder Mortar Z. Fei et al. https://doi.org/10.3390/ma16020583
2487. Prediction of road marking paint retro-reflectivity using novel multi-layer perceptron-integrated quantum harmonic spline Gaussian and fuzzy tree wavelet nonlinear regression framework F. Alharbi et al. https://doi.org/10.1016/j.engappai.2026.115655
2488. Multi-objective optimization for limiting tunnel-induced damages considering uncertainties L. Zhang & P. Lin https://doi.org/10.1016/j.ress.2021.107945
2489. Generating virtual vehicle trajectories for the estimation of emissions and fuel consumption N. Tsanakas et al. https://doi.org/10.1016/j.trc.2022.103615
2490. Evaluating 3D human face reconstruction from a frontal 2D image, focusing on facial regions associated with foetal alcohol syndrome F. Atuhaire et al. https://doi.org/10.17159/sajs.2023/12064
2491. Data-driven modeling of surface roughness in a novel magnetically-assisted externally supplied abrasive-based finishing process R. Babbar et al. https://doi.org/10.1007/s00170-025-16761-8
2492. Explainable artificial intelligence framework for predicting and minimizing CO₂ emissions in GGBFS-geopolymer concrete S. Wani et al. https://doi.org/10.1016/j.advengsoft.2026.104189
2493. Soil health spatial-temporal variation influence soil security on Midwestern, U.S. farms B. Crookston et al. https://doi.org/10.1016/j.soisec.2021.100005
2494. MG-CNFNet: A multiple grained channel normalized fusion networks for medical image deblurring X. Zeng et al. https://doi.org/10.1016/j.bspc.2023.104572
2495. A Hybrid Computational Intelligence Framework for Automatic Calibration of Catchment Scale Hydrodynamic Flood Models M. Sedighkia et al. https://doi.org/10.1007/s40710-026-00880-9
2496. Jitter Decomposition by Convolutional Neural Networks N. Ren et al. https://doi.org/10.1109/TEMC.2020.3047080
2497. Molecular modelling studies of tricyclic triazinone analogues as potential PKC-θ inhibitors through combined QSAR, molecular docking and molecular dynamics simulations techniques L. Meng et al. https://doi.org/10.1016/j.jtice.2018.06.017
2498. A Survey of Generative Adversarial Networks for Synthesizing Structured Electronic Health Records G. Ghosheh et al. https://doi.org/10.1145/3636424
2499. Understanding meteorological drought dynamics in Tekeze watershed using geospatial technology, northern Ethiopia Y. Tela et al. https://doi.org/10.1007/s11069-025-07765-4
2500. Identification-Assisted Sim-to-Real Reinforcement Learning for Adaptive Sliding Mode Control of Industrial Robotic Manipulators D. Tran et al. https://doi.org/10.1109/ACCESS.2026.3729712
2501. Predicting picking and workforce planning for internal shopfloor material logistics – a simulative, data-driven forecasting model P. Eichenseer & H. Winkler https://doi.org/10.1108/JM2-09-2024-0288
2502. Assessing ventilation cavity design impact on the energy performance of rainscreen wall assemblies: A CFD study B. Nghana et al. https://doi.org/10.1016/j.buildenv.2021.107789
2503. A strategy to estimate daily shortwave downward radiation in rugged regions from a few satellite observations Y. Xian et al. https://doi.org/10.1080/15481603.2025.2557700
2504. A New Prediction Method of Industrial Atmospheric Pollutant Emission Intensity Based on Pollutant Emission Standard Quantification T. Ju et al. https://doi.org/10.2139/ssrn.4016135
2505. Assessment of macronutrients status using digital soil mapping techniques: a case study in Maru’ak area in Lorestan Province, Iran A. Salmanpour et al. https://doi.org/10.1007/s10661-023-11145-5
2506. Netizens' behavior towards a blockchain-based esports framework: a TPB and machine learning integrated approach J. Yadav et al. https://doi.org/10.1108/IJSMS-06-2021-0130
2507. A novel spatial optimization approach for the cost-effectiveness improvement of LID practices based on SWMM-FTC S. Li et al. https://doi.org/10.1016/j.jenvman.2022.114574
2508. Machine learning-based digital mapping of soil organic carbon and texture in the mid-Himalayan terrain N. Rengma et al. https://doi.org/10.1007/s10661-023-11608-9
2509. Research on electric vehicle charging load prediction method based on spectral clustering and deep learning network F. Xin et al. https://doi.org/10.3389/fenrg.2024.1294453
2510. CEEMDAN–FADE: A Data-Driven Frequency-Adaptive Ensemble Framework for Carbon-Price Forecasting G. Xu et al. https://doi.org/10.3390/systems14101220
2511. TrGPCR: GPCR–Ligand Binding Affinity Prediction Based on Dynamic Deep Transfer Learning Y. Lu et al. https://doi.org/10.1109/JBHI.2023.3307928
2512. Optimal Nitrogen Application Strategies for Alfalfa Under Different Precipitation Patterns: Balancing Yield, Nitrogen Fertilizer Use Efficiency, and Soil Nitrogen Residue Y. Wang et al. https://doi.org/10.3390/plants15020333
2513. Pavement surface condition estimation based on geospatial modelling S. Zhang et al. https://doi.org/10.1080/19475683.2017.1325404
2514. Estimation of Soil Nutrients and Fertilizer Dosage Using Ion-Selective Electrodes for Efficient Soil Management A. Kumari et al. https://doi.org/10.1080/00103624.2024.2334255
2515. Accuracy of a Novel Smartphone-Based Log Measurement App in the Prototyping Phase M. Elias et al. https://doi.org/10.3390/s25185847
2516. Experimental analysis of the effects of ship motion on hydrogen dispersion in an enclosed area B. Kim & K. Hwang https://doi.org/10.1016/j.ijhydene.2023.04.320
2517. Spatial Predictions and Associated Uncertainty of Annual Soil Respiration at the Global Scale D. Warner et al. https://doi.org/10.1029/2019GB006264
2518. Revisiting kernel complexity in Gaussian process regression: An empirical study on text-to-visual embedding mapping in fashion design D. Mo et al. https://doi.org/10.1016/j.neucom.2026.134304
2519. A Scheduling Algorithm for Appliance Energy Consumption Optimization in a Dynamic Pricing Environment H. Touhs et al. https://doi.org/10.3390/wevj15010001
2520. A case study on canola (Brassica napus L.) potential yield prediction using remote sensing imagery and advanced data analytics N. Rai et al. https://doi.org/10.1016/j.atech.2024.100698
2521. SPRINT: Spectra Preserving Radiance Image Fusion Technique using holistic deep edge spatial attention and Minnaert guided Bayesian probabilistic model I. Misra et al. https://doi.org/10.1016/j.image.2023.116920
2522. Determination of Wastewater Behavior of Large Passenger Ships Based on Their Main Parameters in the Pre-Design Stage V. Şahin & N. Vardar https://doi.org/10.3390/jmse8080546
2523. Hydraulic Performance and Modelling of Pressurized Drip Irrigation System E. Sharu & M. Ab Razak https://doi.org/10.3390/w12082295
2524. Interaction of hydro-socio-technology-knowledge indicators in integrated water resources management using soft-computing techniques M. Zeinali et al. https://doi.org/10.2166/ws.2020.327
2525. Back pain attitudes questionnaire: Cross-cultural adaptation to brazilian-portuguese and measurement properties R. Krug et al. https://doi.org/10.1016/j.bjpt.2020.07.001
2526. Improving daily streamflow simulations for data-scarce watersheds using the coupled SWAT-LSTM approach S. Chen et al. https://doi.org/10.1016/j.jhydrol.2023.129734
2527. High-frequency monitoring reveals recurrent extreme events in a tropical estuary I. Leite Costa et al. https://doi.org/10.1016/j.csr.2026.105655
2528. Street Orientation, Aspect Ratio, and Tree Species Interactions on Heat Exposure in Temperate Monsoon Climate X. Chen et al. https://doi.org/10.3390/su18073177
2529. An evaluation of the performance of a WRF multi-physics ensemble for heatwave events over the city of Melbourne in southeast Australia H. Imran et al. https://doi.org/10.1007/s00382-017-3758-y
2530. A systematic review of personal thermal comfort models L. Arakawa Martins et al. https://doi.org/10.1016/j.buildenv.2021.108502
2531. Ames Test Prediction on High Energy Molecules by On‐The‐Fly QSAR (OTF‐QSAR) C. Alliod et al. https://doi.org/10.1002/prep.201600155
2532. The first HyDRA challenge for computational vibrational spectroscopy T. Fischer et al. https://doi.org/10.1039/D3CP01216F
2533. Estimation of Soil Organic Carbon Using Artificial Neural Networks and Regression Models E. Kahveci & S. Malkoçoğlu https://doi.org/10.17475/kastorman.2047250
2534. Artificial Neural Network and NLR techniques to predict the rheological properties and compression strength of cement past modified with nanoclay A. Mohammed et al. https://doi.org/10.1016/j.asej.2020.07.033
2535. Prediction of Shield Machine Attitude Based on Various Artificial Intelligence Technologies H. Xiao et al. https://doi.org/10.3390/app112110264
2536. Validity of the Perception Neuron inertial motion capture system for upper body motion analysis R. Sers et al. https://doi.org/10.1016/j.measurement.2019.107024
2537. Enhancing Leaf Area Index Estimation for Maize with Tower-Based Multi-Angular Spectral Observations L. Yan et al. https://doi.org/10.3390/s23229121
2538. Hard-Particle Surface Stabilization and Data-Driven Wear Prediction in TiB2-Reinforced Heat-Polymerized PMMA Denture Base Composites E. Hıdır et al. https://doi.org/10.3390/cryst16080494
2539. Analysis of Polarization Characteristics in Outdoor-to-Indoor Wireless Channels for High-Speed Trains Y. Feng et al. https://doi.org/10.1109/LCOMM.2025.3547905
2540. Cluster-Based Machine Learning-Driven Routing for UAV Networks in 6G Environment L. Costa et al. https://doi.org/10.1109/ACCESS.2025.3618800
2541. Filtering harbor craft vessels’ fuel data using statistical, decomposition, and predictive methodologies J. Hadi et al. https://doi.org/10.1016/j.martra.2022.100063
2542. Relationships between response surfaces for tablet characteristics of placebo and API-containing tablets manufactured by direct compression method Y. Hayashi et al. https://doi.org/10.1016/j.ijpharm.2017.08.111
2543. Analysis and assessment of software reliability modeling with preemptive priority queueing policy J. Lin et al. https://doi.org/10.1016/j.jss.2022.111249
2544. Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna V. Odipo et al. https://doi.org/10.3390/f7120294
2545. Purification of crude glycerol derived from biodiesel production process using ceramic membranes: Experimental studies and modeling of flux behavior M. Carolina Sérgi Gomes et al. https://doi.org/10.1016/j.seppur.2024.129042
2546. WRF Simulations of Extreme Rainfall over Uganda’s Lake Victoria Basin: Sensitivity to Parameterization, Model Resolution and Domain Size R. Opio et al. https://doi.org/10.4236/gep.2020.84002
2547. Spatiotemporal prediction of landslide displacement using deep learning approaches based on monitored time-series displacement data: a case in the Huanglianshu landslide N. Xi et al. https://doi.org/10.1080/17499518.2023.2172186
2548. Comparison and evaluation of statistical criteria in the solar cell and photovoltaic module parameters’ extraction M. Louzazni et al. https://doi.org/10.1080/01430750.2018.1517678
2549. Diyabet tanısının tahminlenmesinde denetimli makine öğrenme algoritmalarının performans karşılaştırması Y. ÖZKAN et al. https://doi.org/10.17714/gumusfenbil.820882
2550. Comparative Study of AI-Based Methods—Application of Analyzing Inflow and Infiltration in Sanitary Sewer Subcatchments Z. Zhang et al. https://doi.org/10.3390/su12156254
2551. Physics-informed deep learning for predictive risk perception in tunnel construction P. Lin et al. https://doi.org/10.1016/j.engappai.2025.113715
2552. Improving the Inversion Accuracy of Terrestrial Water Storage Anomaly by Combining GNSS and LSTM Algorithm and Its Application in Mainland China Y. Shen et al. https://doi.org/10.3390/rs14030535
2553. Assessing WQI Using Spatial Land-Use Context Derived from Google Earth Imagery and Advanced Convolutional Neural Networks in South Korea I. Choi et al. https://doi.org/10.3390/su18052377
2554. Comprehensive spatial mapping of metals and metalloids in the Peruvian Mantaro Valley using advanced geospatial data Integration S. Pizarro et al. https://doi.org/10.1016/j.geoderma.2024.117138
2555. Impact of a national tsetse control programme to eliminate Gambian sleeping sickness in Uganda: a spatiotemporal modelling study J. Longbottom et al. https://doi.org/10.1136/bmjgh-2024-015374
2556. Transfer Learning Based on N-BEATS in Forecasting Univariate Time Series M. Lee et al. https://doi.org/10.1109/ACCESS.2026.3675559
2557. Global patterns and edaphic-climatic controls of soil carbon decomposition kinetics predicted from incubation experiments D. Xiang et al. https://doi.org/10.1038/s41467-023-37900-3
2558. A Machine Learning Approach to Determine the Band Gap Energy of High-Entropy Oxides Using UV-Vis Spectroscopy J. Hoyos-Sanchez et al. https://doi.org/10.3390/eng6120340
2559. Validating and Enhancing Extreme Precipitation Projections by Downscaled Global Climate Model Results and Copula Methods H. Hu & B. Ayyub https://doi.org/10.1061/(ASCE)HE.1943-5584.0001803
2560. Validation of satellite based precipitation over diverse topography of Pakistan M. Iqbal & H. Athar https://doi.org/10.1016/j.atmosres.2017.10.026
2561. Evaluation and prediction of hybrid solar-wind energy output using physics-based and machine learning models for reliable power system optimization C. Balakrishna Moorthy et al. https://doi.org/10.1016/j.seta.2026.105353
2562. Predicción de la presión de burbujeo utilizando aprendizaje automático O. Gil https://doi.org/10.48168/innosoft.s11.a82
2563. On the kernel and particle consistency in smoothed particle hydrodynamics L. Di G. Sigalotti et al. https://doi.org/10.1016/j.apnum.2016.05.007
2564. Estimation of Forage Biomass in Oat (Avena sativa) Using Agronomic Variables through UAV Multispectral Imaging J. Urquizo et al. https://doi.org/10.3390/rs16193720
2565. Possible Scenarios of Winter Wheat Yield Reduction of Dryland Qazvin Province, Iran, Based on Prediction of Temperature and Precipitation Till the End of the Century B. Mirgol & M. Nazari https://doi.org/10.3390/cli6040078
2566. Modeling the reactivity of ozone and sulphate radicals towards organic chemicals in water using machine learning approaches S. Gupta & N. Basant https://doi.org/10.1039/C6RA22865H
2567. Spatial Heterogeneity and Drivers of Heavy Metals in Soils and Sediments of the Nyangqu River Basin, Tibetan Plateau, China: Insights from GeoDetector and Explainable Machine Learning J. Chen et al. https://doi.org/10.3390/toxics14080697
2568. Development of optimal parameter determination algorithm for two-dimensional flow analysis model E. Shin et al. https://doi.org/10.1016/j.envsoft.2025.106331
2569. Estimation of the Experimental Drying Performance Parameters Using Polynomial SVM and ANN Models K. ÇERÇİ et al. https://doi.org/10.26701/ems.692149
2570. Assessing trends and variability of rainfall and temperature in the Kafa biosphere reserve, southwest Ethiopia A. Amsalu et al. https://doi.org/10.1007/s43621-025-02499-6
2571. Recent Advances in Silicon Solar Cell Research Using Data Science-Based Learning R. Jaiswal et al. https://doi.org/10.1109/JPHOTOV.2022.3221003
2572. A data-driven machine learning framework for predicting total agricultural food grain yield N. S & J. S https://doi.org/10.1016/j.rineng.2025.106790
2573. Predicting Furniture Prices Using Machine Learning Methods K. Kılıç https://doi.org/10.33484/sinopfbd.1795688
2574. Long-term prediction of daily solar irradiance using Bayesian deep learning and climate simulation data F. Gerges et al. https://doi.org/10.1007/s10115-023-01955-x
2575. An open, reproducible benchmark of daily CO2 forecasting models with applications to GHG monitoring P. Catret-Ruber et al. https://doi.org/10.1016/j.envsoft.2025.106781
2576. Microwave-assisted dilute acid pretreatment of different agricultural bioresources for fermentable sugar production M. Germec et al. https://doi.org/10.1007/s10570-017-1408-5
2577. Future Climatic Projections and Hydrological Responses with a Data Driven Method: A Regional Climate Model Perspective H. Yang et al. https://doi.org/10.1007/s11269-024-03753-8
2578. Machine learning approaches for imputing missing meteorological data in Senegal M. Toure et al. https://doi.org/10.1016/j.acags.2025.100281
2579. An Effective Machine Learning Scheme to Analyze and Predict the Concentration of Persistent Pollutants in the Great Lakes C. Wu et al. https://doi.org/10.1109/ACCESS.2021.3069990
2580. Impact of crop types and irrigation on soil moisture downscaling in water-stressed cropland regions Y. Wang et al. https://doi.org/10.1016/j.eiar.2023.107073
2581. 古气候数据同化: 原理和展望 昊. 张 et al. https://doi.org/10.1360/SSTe-2024-0090
2582. Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey M. Ghorbani et al. https://doi.org/10.1007/s00477-017-1474-0
2583. Robust HRRP Reconstruction for Unmodulated Radar Pulses Based on Spectral Inverse Filtering and Learning V. NGUYEN et al. https://doi.org/10.4316/AECE.2026.01010
2584. Trace-Driven Simulation of LoRaWAN Air Channel Propagation in an Urban Scenario E. Harinda et al. https://doi.org/10.25046/aj050625
2585. Novel application of Google earth engine interpolation algorithm for the development of geotechnical soil maps: a case study of mega-district Z. Ijaz et al. https://doi.org/10.1080/10106049.2022.2138566
2586. Using a deep temporal convolutional network as a building energy surrogate model that spans multiple climate zones P. Westermann et al. https://doi.org/10.1016/j.apenergy.2020.115563
2587. Improved collaborative filtering recommendation algorithm based on differential privacy protection C. Yin et al. https://doi.org/10.1007/s11227-019-02751-7
2588. Spatio-temporal evaluation of open access precipitation products with rain gauge observations in Nigeria A. Salami & A. Fenta https://doi.org/10.1007/s12517-022-11071-9
2589. Comparison of Long Short-Term Memory and Convolutional Neural Network Models for Emergency Department Patients’ Arrival Daily Forecasting S. Moosavi Kashani et al. https://doi.org/10.5812/jamm-140888
2590. Relative Effect of Location Alternatives on Urban Hydrology. The Case of Greater Port-Harcourt Watershed, Niger Delta N. Dan-Jumbo & M. Metzger https://doi.org/10.3390/hydrology6030082
2591. Performance of multi-physics ensembles in convective precipitation events over northeastern Spain E. García-Ortega et al. https://doi.org/10.1016/j.atmosres.2017.02.009
2592. Does agroecosystem model improvement increase simulation accuracy for agricultural N2O emissions? Y. Zhang & Q. Yu https://doi.org/10.1016/j.agrformet.2020.108281
2593. Multi-objective optimization of seeding performance of a pneumatic precision seed metering device using integrated ANN-MOPSO approach C. Pareek et al. https://doi.org/10.1016/j.engappai.2022.105559
2594. An ensemble approach to improve BPNN model precision for predicting compressive strength of high-performance concrete R. Kumar Tipu et al. https://doi.org/10.1016/j.istruc.2022.09.046
2595. High-precision multi-target prediction and interpretability analysis of biomass gasification via ensemble machine learning Y. Guo et al. https://doi.org/10.1016/j.biortech.2025.133863
2596. Basic Statistical Estimation Outperforms Machine Learning in Monthly Prediction of Seasonal Climatic Parameters E. Hussein et al. https://doi.org/10.3390/atmos12050539
2597. Internal Sensing with Exposed Core Fiber Plasmonic Sensor and Machine-Learning Approach for RI Prediction Y. Ali et al. https://doi.org/10.1007/s11468-024-02754-y
2598. Comparative studies of error metrics in variable fidelity model uncertainty quantification J. Hu et al. https://doi.org/10.1080/09544828.2018.1513126
2599. Enhanced 3D Point Cloud Reconstruction for Light Field Microscopy Using U-Net-Based Convolutional Neural Networks S. Imtiaz et al. https://doi.org/10.32604/csse.2023.040205
2600. Hybrid Radial Basis Function Neural Networks for Urban Traffic Signal Control B. Gencosman https://doi.org/10.36909/jer.v8i4.8349
2601. Advances in Real-Time 3D Reconstruction for Medical Endoscopy A. Richter et al. https://doi.org/10.3390/jimaging10050120
2602. Retinal Mosaicking with Vascular Bifurcations Detected on Vessel Mask by a Convolutional Network X. Feng et al. https://doi.org/10.1155/2020/7156408
2603. Building life-span prediction for life cycle assessment and life cycle cost using machine learning: A big data approach S. Ji et al. https://doi.org/10.1016/j.buildenv.2021.108267
2604. Usage of Clustering and Weighted Nearest Neighbors for Efficient Missing Data Imputation of Microarray Gene Expression Dataset A. Dubey & A. Rasool https://doi.org/10.1002/adts.202200460
2605. The Use of Forest Biomass for Energy Purposes in Selected European Countries A. Kożuch et al. https://doi.org/10.3390/en16155776
2606. Edge-Carrier-Assisted Phase Retrieval at Low-CSPR and Low-Dispersion Diversity With Deep Learning D. Orsuti et al. https://doi.org/10.1109/JLT.2023.3335394
2607. Accuracy and inter-cloud precision of low-cost mobile LiDAR technology in estimating soil disturbance in forest operations G. Forkuo & S. Borz https://doi.org/10.3389/ffgc.2023.1224575
2608. Investigating the Optimal Spatial Resolution for Assimilating GNSS PWV into an NWP System to Improve the Accuracy of Humidity Field H. Li et al. https://doi.org/10.1109/JSTARS.2023.3298489
2609. Hydrodynamic and Waves Response during Storm Surges on the Southern Brazilian Coast: A Hindcast Study A. de Lima et al. https://doi.org/10.3390/w12123538
2610. A geographically weighted XGBoost framework for Pixel-Level modeling of vegetation responses using Multi-Source Earth Observation data Y. Khosravi & T. Ouarda https://doi.org/10.1016/j.isprsjprs.2026.03.006
2611. Short-term wind power forecasting with lag-based feature engineering: a turbine-level machine learning comparison E. Demir & S. Akkaya Oy https://doi.org/10.1007/s00521-026-12356-w
2612. Reconstruction of Missing Hourly Precipitation Data to Increase Training Data Set for ANN H. Nagaraja et al. https://doi.org/10.4018/IJAEIS.2018010104
2613. RETRACTED: Bone Age Assessment Based on Deep Convolutional Features and Fast Extreme Learning Machine Algorithm L. Guo et al. https://doi.org/10.3389/fenrg.2021.813650
2614. Development of Mesoporous Geo-Adsorbent Pellets from Low Fire Clay and Cellulose for Removal of Methylene Blue in Aquaculture P. Sharma & K. Qanungo https://doi.org/10.14233/ajchem.2021.23322
2615. Climate Dynamics and Rain-fed Tuber Crop Yield Cultivated by Small-scale Landowner Under Global Warming in Wolaita Zone Southern Ethiopia T. Badacho https://doi.org/10.11648/j.ajere.20251002.12
2616. Development of a coupled aerosol lidar data quality assurance and control scheme with Monte Carlo analysis and bilateral filtering H. Wang et al. https://doi.org/10.1016/j.scitotenv.2020.138844
2617. Experimental and Statistical Investigations for Tensile Properties of Hemp Fibers P. Sadeghi et al. https://doi.org/10.3390/fib12110094
2618. Fusing Time and Distribution Domains: A Feature-Interaction Network for Jitter Component Analysis R. Wu et al. https://doi.org/10.1109/TEMC.2026.3679020
2619. Performance assessment of panel-based discontinuous geofoam-infilled trenches for near-field ground vibration mitigation A. Singh et al. https://doi.org/10.1016/j.jobe.2026.117356
2620. New semiempirical temporal model to predict chloride profiles considering convection and diffusion zones T. Reichert et al. https://doi.org/10.1016/j.conbuildmat.2022.130284
2621. Leveraging Climate Data Through Intelligent Systems for the Prediction of Arbovirus Transmission by Aedes aegypti C. Lima et al. https://doi.org/10.3390/ijerph23010012
2622. Spatiotemporal dynamics of climate-driven irrigation requirements for maize in Mymensingh, Bangladesh: A GIS-based multi-model general circulation ensemble projection approach M. Islam et al. https://doi.org/10.1016/j.rineng.2026.110970
2623. Dynamic Soft Sensing of Stack NOx Concentration in Cement Kiln SNCR–SCR Denitrification Using a DAC-IVY-Optimized TCN-SE-LSTM Model Z. Zhao et al. https://doi.org/10.3390/pr14132176
2624. A comprehensive approach for predicting local scour depth using machine learning models V. Bhardwaj et al. https://doi.org/10.1088/2631-8695/ae4b0d
2625. Design and implementation of a hybrid FLC + PID controller for pressure control of sleep devices A. Golcuk https://doi.org/10.1016/j.bspc.2022.103702
2626. Predictive analysis and performance assessment of coal bottom ash in recycled aggregate concrete under elevated temperatures A. Saxena et al. https://doi.org/10.1007/s11356-025-37374-4
2627. Large-scale water quality prediction with integrated deep neural network J. Bi et al. https://doi.org/10.1016/j.ins.2021.04.057
2628. Predicting and Explaining Pig Iron Production on Charcoal Blast Furnaces: A Machine Learning Approach M. Salles Melo Lima et al. https://doi.org/10.1287/inte.2020.1058
2629. A new approach for product reliability prediction by considering the production factory lifecycle information S. Gunjan et al. https://doi.org/10.1016/j.ress.2025.110915
2630. Enhancing the Human Health Status Prediction: The ATHLOS Project P. Anagnostou et al. https://doi.org/10.1080/08839514.2021.1935591
2631. Inverse Thermal Modeling to Determine Power Losses in Induction Motor D. Nair & A. Arkkio https://doi.org/10.1109/TMAG.2017.2661381
2632. On random-parameter count models for out-of-sample crash prediction: Accounting for the variances of random-parameter distributions P. Xu et al. https://doi.org/10.1016/j.aap.2021.106237
2633. Effect of furfural concentration on ethanol production using Saccharomyces cerevisiae in an immobilized cells stirred‐tank bioreactor with glucose‐based medium and mathematical modeling S. Erkan et al. https://doi.org/10.1111/jfpp.14635
2634. Understanding Digital Banking Decision-Making System Through Artificial Neural Networks S. Ghita-Mitrescu et al. https://doi.org/10.3390/systems14091068
2635. The hydrology of sand rivers in Zimbabwe and the use of remote sensing to assess their level of saturation S. Mpala et al. https://doi.org/10.1016/j.pce.2016.03.004
2636. Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa S. Sazawal et al. https://doi.org/10.1186/s12884-021-04067-y
2637. Bio-based derived activated carbon electrodes for azo dye removal: Enhanced electrocoagulation via hybrid statistical–machine learning framework F. Dadpanah & S. Sadri Moghaddam https://doi.org/10.1016/j.jwpe.2025.108283
2638. Multi-Scale Cascaded With Cross-Attention Network-Based Deformation Vector Field Estimation for Motion-Compensated 4D-CBCT Reconstruction P. Yuan et al. https://doi.org/10.1109/TCI.2025.3561660
2639. Analyzing the impact of activation functions on the performance of the data-driven gait model B. Singh et al. https://doi.org/10.1016/j.rineng.2023.101029
2640. Time series decomposition of remotely sensed land surface temperature and investigation of trends and seasonal variations in surface urban heat islands J. Quan et al. https://doi.org/10.1002/2015JD024354
2641. A Novel Hybrid Framework for Short-Term Carbon Emissions Forecasting in China: Aggregate and Sectoral Perspectives L. Guo & G. Xu https://doi.org/10.3390/su172210206
2642. Atomistic Descriptors for Machine Learning Models of Solubility Parameters for Small Molecules and Polymers M. Chi et al. https://doi.org/10.3390/polym14010026
2643. A New Approach to Calibrating Functional Complexity Weight in Software Development Effort Estimation V. Hai et al. https://doi.org/10.3390/computers11020015
2644. Reduced-order modeling of steam turbine rotor based on Hybrid-DeepONet architecture J. Yan et al. https://doi.org/10.1016/j.csite.2026.107949
2645. Efficiency evaluation of reverse osmosis desalination plant using hybridized multilayer perceptron with particle swarm optimization M. Ehteram et al. https://doi.org/10.1007/s11356-020-08023-9
2646. Machine‐learning random forest algorithms predict post‐cycloplegic myopic corrections from noncycloplegic clinical data Y. Hao et al. https://doi.org/10.1097/OPX.0000000000002230
2647. A stochastic differential equation approach to the analysis of the 2017 and 2019 UK general election polls M. Levene & T. Fenner https://doi.org/10.1016/j.ijforecast.2021.02.002
2648. An Ensemble Sensitivity Analysis for Optimizing Physical Schemes in Summer Heavy Rainfall Predictions Over DPR Korea K. Jo et al. https://doi.org/10.1002/met.70181
2649. Monitoring the growth of Fusarium graminearum in wheat kernels using multispectral imaging with chemometric methods W. Liu et al. https://doi.org/10.1039/D1AY01586A
2650. A hyperspectral pansharpening method using retrain transformer network for remote sensing images in UAV communications system Y. Feng et al. https://doi.org/10.1007/s11276-023-03611-2
2651. Camouflage Object Segmentation Using an Optimized Deep-Learning Approach M. Kamran et al. https://doi.org/10.3390/math10224219
2652. Machine Learning Based Simulation for Design Space Exploration O. Bleisinger et al. https://doi.org/10.1017/pds.2022.154
2653. Bayesian Model Averaging: A Unique Model Enhancing Forecasting Accuracy for Daily Streamflow Based on Different Antecedent Time Series S. Kim et al. https://doi.org/10.3390/su12229720
2654. A Data-Driven Approach to Close the Water Balance of a Cascaded Multiple Reservoir–Lake System M. Chappon et al. https://doi.org/10.3390/hydrology13070191
2655. Cluster-Based Analogue Ensembles for Hindcasting with Multistations C. Balsa et al. https://doi.org/10.3390/computation10060091
2656. Decision making methodology for maintenance of return pumps in wastewater treatment plant using machine learning S. Yang et al. https://doi.org/10.1016/j.scitotenv.2025.180940
2657. The effects of group adaptation on task performance: An agent-based approach D. Blanco-Fernández et al. https://doi.org/10.1371/journal.pone.0290578
2658. The Detection and Counting of Olive Tree Fruits Using Deep Learning Models in Tacna, Perú E. Osco-Mamani et al. https://doi.org/10.3390/ai6020025
2659. Accuracy Verification and Correction of a Depth-Camera-Based Digital Measurement System for Pelvic Balance Assessment in the Trendelenburg Test J. Kim et al. https://doi.org/10.3390/electronics15173988
2660. A Residual-Based Hybrid BiLSTM–XGBoost Model for Multivariate Dam Fill Rate Forecasting: The Case of Istanbul H. Canlı https://doi.org/10.29130/dubited.1809519
2661. Prediction of the Vertical Bearing Capacity of Piles in Cold Saline Environments by a Multi-Dimensional Machine Learning Approach Y. Jia & Z. Li https://doi.org/10.3390/buildings16102042
2662. Impact of data correlation on privacy budget allocation in continuous publication of location statistics D. Hemkumar et al. https://doi.org/10.1007/s12083-021-01078-6
2663. Membraneless Microbial Fuel Cell: Characterization of Electrogenic Bacteria and Kinetic Growth Model M. Mohd Zaini Makhtar & V. Vadivelu https://doi.org/10.1061/(ASCE)EE.1943-7870.0001522
2664. Photovoltaic Energy Production Forecasting through Machine Learning Methods: A Scottish Solar Farm Case Study L. Cabezón et al. https://doi.org/10.3390/en15228732
2665. Neural network modeling and prediction of HfO 2 thin film properties tuned by thermal annealing M. Gao et al. https://doi.org/10.1017/hpl.2024.6
2666. Leveraging WiFi network logs to infer student collocation and its relationship with academic performance V. Das Swain et al. https://doi.org/10.1140/epjds/s13688-023-00398-2
2667. Canopy gap monitoring in Central African tropical forests using pocket drones: Reliability depends on scale T. Besisa Nguba et al. https://doi.org/10.1016/j.geomat.2026.100133
2668. Examination of empirical and Machine Learning methods for regression of missing or invalid solar radiation data using routine meteorological data as predictors K. Soulis et al. https://doi.org/10.3934/geosci.2024044
2669. Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model L. Diaz et al. https://doi.org/10.3390/atmos12111436
2670. Inverted Algorithm of Groundwater Storage Anomalies by Combining the GNSS, GRACE/GRACE-FO, and GLDAS: A Case Study in the North China Plain Y. Shen et al. https://doi.org/10.3390/rs14225683
2671. Machine learning-based multi-domain model for SOT composite score prediction using quiet standing COP data Y. Cho et al. https://doi.org/10.1007/s13534-026-00555-2
2672. Time versus Space: Choice of Effort Metric Can Avoid Bias in Boat Electrofishing Catch per Unit Effort B. Marcy-Quay et al. https://doi.org/10.1002/nafm.10351
2673. Hydro-Climatic variability in the Potohar Plateau of Indus River Basin under CMIP6 climate projections A. Khan et al. https://doi.org/10.1007/s00704-024-05274-1
2674. Online chicken carcass volume estimation using depth imaging and 3-D reconstruction I. Nyalala et al. https://doi.org/10.1016/j.psj.2024.104232
2675. Predictive modeling and interpretation of LC3-ECC compressive strength using XGBoost and gene expression programming Z. Liu et al. https://doi.org/10.1016/j.mtcomm.2025.113842
2676. Kinetic mechanism of fine limestone in fluidized bed calcination: Surface reaction dominance T. Chen et al. https://doi.org/10.1016/j.cherd.2025.10.031
2677. Applying quantitative structure models to plot-based terrestrial laser data to assess dendrometric parameters in dense mixed forests C. Torresan et al. https://doi.org/10.5424/fs/2018271-12658
2678. Taşkın Verilerinin Modellenmesinde MEP Yönteminin Kullanılabilirliğinin Araştırılması A. Kizilkaya et al. https://doi.org/10.55007/dufed.1680507
2679. Automating traffic monitoring with SHM sensor networks via vision-supervised deep learning H. Wu et al. https://doi.org/10.1016/j.measurement.2026.123364
2680. Generalised spatial error for validation H. Liu et al. https://doi.org/10.1080/15481603.2026.2690327
2681. Comparative QSAR and Q-RASAR modeling of benzimidazole derivatives as dual AChE/BuChE inhibitors and design of novel anti- Alzheimer drug candidates supported by molecular docking, ADMET and molecular dynamic simulation S. Ilaghi-Hoseini & Z. Garkani-Nejad https://doi.org/10.1016/j.jmgm.2026.109550
2682. An intelligent sensing system for indoor ozone removal by dynamic flow field management and physics-informed network with focused-differential attention S. Sun et al. https://doi.org/10.1016/j.jobe.2026.116097
2683. Customer decision-making analysis based on big social data using machine learning: a case study of hotels in Mecca A. Alsayat https://doi.org/10.1007/s00521-022-07992-x
2684. Assessing the vulnerability of Elasmobranch species in the Bay of Bengal: Insights from Lakkha gill net fishery of Bangladesh R. Das et al. https://doi.org/10.1016/j.heliyon.2024.e37331
2685. In-silico identification of a Doxorubicin alternative with reduced cardiotoxicity informed by LLM-assisted modeling D. Das & D. Chakraborty https://doi.org/10.1016/j.jmgm.2025.109217
2686. Overinterpretation of evaluation results in machine learning studies for maize yield prediction: A systematic review J. Leukel et al. https://doi.org/10.1016/j.compag.2024.109892
2687. Assessment of the Impact of Climatic Variations on the Photovoltaic Potential of Kankan (Guinea) Using NASA POWER Data and Artificial Neural Network (2000–2025) P. Sow et al. https://doi.org/10.11648/j.sjee.20261403.12
2688. Benchmarking GHG Emissions Forecasting Models for Global Climate Policy C. Tudor & R. Sova https://doi.org/10.3390/electronics10243149
2689. Short-term soil moisture content forecasting with a hybrid informer model L. Wang et al. https://doi.org/10.3389/fsufs.2025.1636499
2690. Determining factors of the blood feeding behaviour of mosquito vectors of West Nile and Rift Valley fever viruses in Madagascar L. Tantely et al. https://doi.org/10.1038/s41598-026-46448-3
2691. Quantification of CO2 Fluxes in Agroecosystems: A Machine Learning Approach in the Southern Brazilian Pampa O. Ojo et al. https://doi.org/10.1007/s41748-026-01315-z
2692. Current stance on predictive analytics in higher education: opportunities, challenges and future directions R. Umer et al. https://doi.org/10.1080/10494820.2021.1933542
2693. Investigation of the energetic performance of an attached solar greenhouse through monitoring and simulation O. Asa'd et al. https://doi.org/10.1016/j.esd.2019.09.001
2694. AirQuaNet: A Convolutional Neural Network Model With Multi-Scale Feature Learning and Attention Mechanisms for Air Quality-Based Health Impact Prediction S. Chadalavada et al. https://doi.org/10.1109/ACCESS.2025.3574722
2695. Prediction of 3D Airspace Occupancy Using Machine Learning C. Tafur et al. https://doi.org/10.3390/forecast7040056
2696. Predicting medical waste amounts and costs using machine learning and XAI for sustainable waste management in healthcare İ. Uysal et al. https://doi.org/10.1007/s13762-025-06895-3
2697. Forecasting pan evaporation with an integrated artificial neural network quantum-behaved particle swarm optimization model: a case study in Talesh, Northern Iran M. Ali Ghorbani et al. https://doi.org/10.1080/19942060.2018.1517052
2698. Intelligent Prediction Model of Coal Spontaneous Combustion Based on Machine Learning C. Zhang et al. https://doi.org/10.1080/00102202.2025.2592277
2699. Practical Machine Learning Application for Predicting Axial Capacity of Composite Concrete-Filled Steel Tube Columns Considering Effect of Cross-Sectional Shapes T. Duong et al. https://doi.org/10.1007/s13296-022-00693-0
2700. Long-term policy guidance for sustainable energy transition in Nigeria: A deep learning-based peak load forecasting with econo-environmental scenario analysis I. Bayode et al. https://doi.org/10.1016/j.energy.2025.135707
2701. Application of XGBoost model for in-situ water saturation determination in Canadian oil-sands by LF-NMR and density data S. Markovic et al. https://doi.org/10.1038/s41598-022-17886-6
2702. Reusability check-based refinement of a biophysical fishpond model P. Sharma et al. https://doi.org/10.1016/j.compag.2024.108664
2703. Validity and reliability of sprint force-velocity profiling in elite football: Comparison of MySprint, GPS, and radar devices R. Stockdale et al. https://doi.org/10.1371/journal.pone.0325611
2704. Planting Age Identification and Yield Prediction of Apple Orchard Using Time-Series Spectral Endmember and Logistic Growth Model X. Gao et al. https://doi.org/10.3390/rs15030642
2705. Artificial Intelligence Design for Ship Structures: A Variant Multiple-Input Neural Network-Based Ship Resistance Prediction Y. Ao et al. https://doi.org/10.1115/1.4053816
2706. Thermal and energy performance of vehicles with spectrally selective coatings under seasonal parking and driving conditions S. Jiao et al. https://doi.org/10.1016/j.energy.2026.142654
2707. Identifying socioeconomic and biophysical factors driving forest loss in protected areas K. Powlen et al. https://doi.org/10.1111/cobi.14058
2708. Reservoir Storage Forecasting Using Machine Learning in the Troy Region, Türkiye U. Mucan https://doi.org/10.3390/su18189407
2709. Hybrid gradient boosting with meta-heuristic algorithms prediction of unconfined compressive strength of stabilized soil based on initial soil properties, mix design and effective compaction V. Tran https://doi.org/10.1016/j.jclepro.2022.131683
2710. Non-invasive regional parameter identification of degenerated human meniscus J. Schwer et al. https://doi.org/10.1016/j.compbiomed.2024.109230
2711. Time series forecasting of weight for diuretic dose adjustment using bidirectional long short-term memory H. Choi et al. https://doi.org/10.1038/s41598-024-68663-6
2712. Speeded-Up Robust Features-based image mosaic method for large-scale microscopic hyperspectral pathological imaging Q. Zhang et al. https://doi.org/10.1088/1361-6501/abc868
2713. Long-term capacitance variation characteristics, law extraction, single and collaborative prediction of film capacitors at room temperature and humidity Y. Zhang et al. https://doi.org/10.1016/j.microrel.2022.114845
2714. A multipoint prediction model for nonlinear displacement of concrete dam K. Yao et al. https://doi.org/10.1111/mice.12911
2715. Numerical simulation of the hybrid ship power distribution system and an analysis of its emission reduction potential O. Yuksel & B. Koseoglu https://doi.org/10.1080/17445302.2022.2028435
2716. An Improved VMD-LSTM Model for Time-Varying GNSS Time Series Prediction with Temporally Correlated Noise H. Chen et al. https://doi.org/10.3390/rs15143694
2717. Estimation of Hydraulic and Water Quality Parameters Using Long Short-Term Memory in Water Distribution Systems N. Sadiki & D. Jang https://doi.org/10.3390/w16213028
2718. A Review of Remote Sensing Image Translation Based on Generative Adversarial Networks Z. Wang et al. https://doi.org/10.3390/rs18193388
2719. Employing large language models for emotion detection in psychotherapy transcripts C. Lalk et al. https://doi.org/10.3389/fpsyt.2025.1504306
2720. Environmentally informed prediction of ultimate bearing capacity using Kernel-SVM and PLAXIS 3D FEM for sustainable geotechnical design D. Ahmed et al. https://doi.org/10.1007/s44288-026-00726-9
2721. A comparative analysis of real and theoretical data in offshore wind energy generation F. Camilo et al. https://doi.org/10.1016/j.prime.2025.100901
2722. iBike: Intelligent public bicycle services assisted by data analytics Y. Zhang et al. https://doi.org/10.1016/j.future.2018.12.017
2723. A Data-Driven Model for Rapid CII Prediction M. Mühmer et al. https://doi.org/10.3390/jmse12112048
2724. Analysis of thermal conductivity of aluminum alloys by compositions and tempering process using machine learning A. Shawon et al. https://doi.org/10.1038/s41598-025-15868-y
2725. Intelligent Control of Groundwater in Slopes with Deep Reinforcement Learning A. Biniyaz et al. https://doi.org/10.3390/s22218503
2726. Simulation-based evaluation of indoor positioning systems in connected aircraft cabins P. Schwarzbach et al. https://doi.org/10.1080/21680566.2024.2321454
2727. Modeling Air–Sea Turbulent Fluxes: Sensitivity to Surface Roughness Parameterizations X. Yang et al. https://doi.org/10.3390/jmse14030277
2728. Electrical Load Forecasting Over Multihop Smart Metering Networks With Federated Learning R. Rahman et al. https://doi.org/10.1109/JIOT.2025.3586115
2729. Heterogeneity Matters: Predicting Self-Esteem in Online Interventions Based on Ecological Momentary Assessment Data V. Bremer et al. https://doi.org/10.1155/2019/3481624
2730. Analysis of indirect method for estimation of X-ray spectrum G. Silva et al. https://doi.org/10.1016/j.apradiso.2025.112087
2731. Improving the Resolution of GRACE/InSAR Groundwater Storage Estimations Using a New Subsidence Feature Weighted Combination Scheme Q. Wang et al. https://doi.org/10.3390/w15061017
2732. Sensor BMP280 Statistical Analysis for Barometric Pressure Acquisition H. Kusuma et al. https://doi.org/10.1088/1755-1315/1148/1/012008
2733. Flood Forecasting Using Artificial Intelligence (AI): A Prisma – Guided Systematic Review S. Mishra & P. Patri https://doi.org/10.2478/ers-2026-0020
2734. Forecasting stock market behavior in BRICS economies using artificial neural machine learning models S. Panigrahi et al. https://doi.org/10.1108/JBSED-05-2025-0134
2735. Simulated Annealing-Optimized LSTM for Large-Scale Temperature Forecasting Across Türkiye V. Demir https://doi.org/10.3390/w18111256
2736. Application of novel hybrid artificial intelligence algorithms to groundwater simulation R. Dehghani & H. Torabi Poudeh https://doi.org/10.1007/s13762-021-03596-5
2737. Potential Use of Artificial Neural Networks in Prediction of Dengue Abundance in Agra District T. Sant & N. Satsangi https://doi.org/10.1088/1757-899X/1116/1/012201
2738. A hybrid XGBoost-based model approach to evaluate the effect of biomass fly ash in vegetable and fruit waste composting H. Doğan et al. https://doi.org/10.1016/j.biombioe.2025.108265
2739. Station-based assessment of reanalysis surface air temperature and warming trends over the Tibetan Plateau (1980–2018) S. Zhang et al. https://doi.org/10.1016/j.jhydrol.2026.135812
2740. ClimaCropNet: A Two-Stage Hybrid Deep Learning and Stacked-Ensemble Framework for Crop Yield and Market-Price Forecasting under Climate Variability in a Data-Scarce Tropical District A. Ayuba & A. Makinde https://doi.org/10.36615/mn47k202
2741. Dissecting the characteristics and driver factors of potential vegetation water use efficiency in China R. Kong et al. https://doi.org/10.1016/j.scitotenv.2024.176174
2742. Explainable deep learning analysis of network depth effects on neutron porosity prediction M. Chowdhury & M. Islam https://doi.org/10.1007/s44288-026-00591-6
2743. Air Pollution Variation During COVID-19 Pandemic Using Satellite and On-site Measurement Data in Six Provinces in Iran M. Zare Shahne et al. https://doi.org/10.61186/NMCE.2407.1067
2744. Adaptive-Attention Completing Network for Remote Sensing Image W. Huang et al. https://doi.org/10.3390/rs15051321
2745. Rumen liquor from slaughtered cattle as inoculum for feed evaluation P. Lutakome et al. https://doi.org/10.1016/j.aninu.2017.06.010
2746. Role of Mineral–Organic Interactions in PFAS Retention by AFFF-Impacted Soil T. Wanzek et al. https://doi.org/10.1021/acs.est.2c08806
2747. Rapid and nondestructive determination of deoxynivalenol (DON) content in wheat using multispectral imaging (MSI) technology with chemometric methods Y. Shi et al. https://doi.org/10.1039/D0AY00859A
2748. Nowcasting of deep convective clouds and heavy precipitation: Comparison study between NWP model simulation and extrapolation V. Bližňák et al. https://doi.org/10.1016/j.atmosres.2016.10.003
2749. Assessing Unconfined Vapor Cloud Explosions (Uvce) Physical Effects: A Software Built For Modelling With Bst Methodology T. Kepekli https://doi.org/10.29109/gujsc.1077377
2750. A Hybrid Algorithm for Missing Data Imputation and Its Application to Electrical Data Loggers C. Turrado et al. https://doi.org/10.3390/s16091467
2751. Uncertainty analysis for landscape models used for coastal planning E. Meselhe et al. https://doi.org/10.1016/j.ecss.2021.107371
2752. Evaluating statistical models to measure environmental change: A tidal turbine case study H. Linder & J. Horne https://doi.org/10.1016/j.ecolind.2017.09.041
2753. Comparing machine learning and classical methods in forecasting Türkiye’s macroeconomic performance E. Kıratoğlu https://doi.org/10.26466/opusjsr.1825433
2754. Localizing Event-Related Potentials Using Multi-source Minimum Variance Beamformers: A Validation Study A. Herdman et al. https://doi.org/10.1007/s10548-018-0627-x
2755. Graph attention networks decode conductive network mechanism and accelerate design of polymer nanocomposites T. Sui et al. https://doi.org/10.1038/s41524-025-01773-5
2756. Tests of Belt Linear Speed for Identification of Frictional Contact Phenomena P. Bortnowski et al. https://doi.org/10.3390/s20205816
2757. Predicting Wastewater Influent Characteristics Using Data-Driven Modeling Approaches O. El-Dakhakhni et al. https://doi.org/10.3390/w18111255
2758. Comparing the mapping between EQ-5D-5L, EQ-5D-3L and the EORTC-QLQ-C30 in non-small cell lung cancer patients I. Khan et al. https://doi.org/10.1186/s12955-016-0455-1
2759. Mobile Measurement of Particulate Matter Concentrations on Urban Streets: System Development and Field Verification Y. Chiang et al. https://doi.org/10.1109/ACCESS.2020.3034489
2760. Predicting distribution and relative abundance of mid-trophic level organisms using oceanographic parameters and acoustic backscatter P. Escobar-Flores et al. https://doi.org/10.3354/meps12519
2761. Acquisition of physical kinetics in reciprocating machines using reservoir computing for anomaly detection S. Tatsumi et al. https://doi.org/10.1587/nolta.16.848
2762. Vegetation health conditions assessment and mapping using AVIRIS-NG hyperspectral and field spectroscopy data for -environmental impact assessment in coal mining sites N. Kayet et al. https://doi.org/10.1016/j.ecoenv.2022.113650
2763. A Privacy-Preserving Multi-Task Framework for Knowledge Graph Enhanced Recommendation B. Yu et al. https://doi.org/10.1109/ACCESS.2020.3004250
2764. Robust least square modelling for selected daytime ionospheric parameters using geomagnetic observations at low latitudes S. Bello et al. https://doi.org/10.1016/j.asr.2023.04.040
2765. Predictive Modelling of Sugar Release from Blended Garden Wastes in a Microwave-Assisted Hot Water Process R. Bai et al. https://doi.org/10.1007/s12649-019-00932-2
2766. Adaptive layer-based computer-generated holograms Y. Yao et al. https://doi.org/10.1364/OL.509961
2767. Energy Forecasting in a Public Building: A Benchmarking Analysis on Long Short-Term Memory (LSTM), Support Vector Regression (SVR), and Extreme Gradient Boosting (XGBoost) Networks J. Huang et al. https://doi.org/10.3390/app12199788
2768. Model-based yield gap analysis and constraints of rainfed sorghum production in Southwest Ethiopia A. Habte et al. https://doi.org/10.1017/S0021859621000435
2769. Numerical modeling of nutrient transport to assess the agricultural impact on the trophic state of reservoirs F. Torres-Bejarano et al. https://doi.org/10.1016/j.iswcr.2022.06.002
2770. Performance of machine learning algorithms on neutron activations for Germanium isotopes R. Gargouri et al. https://doi.org/10.1016/j.radphyschem.2023.110860
2771. One month-ahead electricity price forecasting in the context of production planning T. Windler et al. https://doi.org/10.1016/j.jclepro.2019.117910
2772. Applied machine learning model comparison: Predicting offshore platform integrity with gradient boosting algorithms and neural networks A. Dyer et al. https://doi.org/10.1016/j.marstruc.2021.103152
2773. Improvements of 6S Look-Up-Table Based Surface Reflectance Employing Minimum Curvature Surface Method K. Lee et al. https://doi.org/10.1007/s13143-019-00164-3
2774. Predicting clinical symptoms of attention deficit hyperactivity disorder based on temporal patterns between and within intrinsic connectivity networks X. Wang et al. https://doi.org/10.1016/j.neuroscience.2017.08.038
2775. Estimation of Bearing Capacity of Piles in Cohesionless Soil Using Optimised Machine Learning Approaches N. Kardani et al. https://doi.org/10.1007/s10706-019-01085-8
2776. An urban-level prediction of lockdown measures impact on the prevalence of the COVID-19 pandemic S. Pourroostaei Ardakani et al. https://doi.org/10.1186/s41118-022-00174-6
2777. AI-driven social media text analysis during crisis: A review for natural disasters and pandemics J. Wahid et al. https://doi.org/10.1016/j.asoc.2025.112774
2778. Regression and Correlation-Based Modeling of Nonlinear Optical Response in Quantum Wells M. Sayraç & E. Yalçın https://doi.org/10.17776/csj.1662124
2779. Improving LSMA for impervious surface estimation in an urban area J. Wang et al. https://doi.org/10.1080/22797254.2021.2018666
2780. Personality trait and state associations with cognitive functioning and variability in middle-aged and older adults W. Ma et al. https://doi.org/10.1093/geronb/gbag179
2781. Mapping Uncertainty Due to Missing Data in the Global Ocean Health Index M. Frazier et al. https://doi.org/10.1371/journal.pone.0160377
2782. Modeling of Medical Waste Generation in Dental Clinics Affiliated to the Provincial Health Directorate in Kastamonu: PLS and Gradient Boosting Approaches E. Kalkan et al. https://doi.org/10.3390/pr13123820
2783. Performance Analysis of IoT-Based pH and EC Control System for Smart Indoor Hydroponics Pagoda Mustard Cultivation B. Muhammad Akbar et al. https://doi.org/10.35970/jinita.v8i1.3080
2784. Use of in vivo video image analysis as a substitute for manual biometric measurements on the prediction of qualitative and quantitative carcass characteristics of hair sheep lambs J. Araújo et al. https://doi.org/10.1016/j.smallrumres.2022.106779
2785. Generating 3D city models without elevation data F. Biljecki et al. https://doi.org/10.1016/j.compenvurbsys.2017.01.001
2786. A Vine Copula Framework for Non-Stationarity Detection Between Precipitation and Meteorological Factors and Possible Driving Factors Y. Liu et al. https://doi.org/10.3390/atmos16111262
2787. Balancing Utility and Privacy: A Semantic-Aware Personalized Trajectory Synthesis Scheme J. Li et al. https://doi.org/10.1109/TMC.2026.3722711
2788. Mathematical modeling of lactic acid fermentation in bioreactor with carob extract M. Germec et al. https://doi.org/10.1016/j.bcab.2018.03.018
2789. Formation and Disruption of Wide Binaries in Star Clusters Revealed by N-body Simulations A. Bissekenov et al. https://doi.org/10.3847/2041-8213/ae5819
2790. Distributional Regression Forests Approach to Regional Frequency Analysis With Partial Duration Series K. Kiran & V. Srinivas https://doi.org/10.1029/2021WR029909
2791. An Ensemble Method for Missing Data of Environmental Sensor Considering Univariate and Multivariate Characteristics C. Choi et al. https://doi.org/10.3390/s21227595
2792. Evaluation of Catch Efficiency Transfer Functions for Unshielded and Single-Alter-Shielded Solid Precipitation Measurements A. Pierre et al. https://doi.org/10.1175/JTECH-D-18-0112.1
2793. Crude Oil Prices Forecasting: An Approach of Using CEEMDAN-Based Multi-Layer Gated Recurrent Unit Networks H. Lin & Q. Sun https://doi.org/10.3390/en13071543
2794. Lag effect of the El Niño–Southern Oscillation on the catch per unit effort of Yellowfin Tuna and Bigeye Tuna in the western and central Pacific longline fisheries J. Zhang et al. https://doi.org/10.1093/mcfafs/vtaf048
2795. Spatial Disaggregation of Historical Census Data Leveraging Multiple Sources of Ancillary Information J. Monteiro et al. https://doi.org/10.3390/ijgi8080327
2796. Machine learning–assisted sustainable removal of cationic dyes using Butea monosperm a leaf powder as an eco-friendly biosorbent P. Mandale et al. https://doi.org/10.1007/s13738-026-03589-6
2797. Correlation between estimated clay contents and hydrometer measurements F. Thaimo & S. Ekolu https://doi.org/10.1680/jgeen.20.00099
2798. A machine learning enhanced time series model for Nigerian unemployment rate prediction B. Ogunbona et al. https://doi.org/10.64497/jssci.79
2799. DC coefficient recovery for JPEG images in ubiquitous communication systems H. Qiu et al. https://doi.org/10.1016/j.future.2019.01.037
2800. Development of Data Prediction Model for the Lubrication System in a Developmental Gas Turbine Engine U. Srinivasan et al. https://doi.org/10.61653/joast.v72i1.2020.80
2801. IoT-Agro: A smart farming system to Colombian coffee farms J. Rodríguez et al. https://doi.org/10.1016/j.compag.2021.106442
2802. Introduction of the neural framework for stationary and nonstationary probability distribution modelling of hydroclimatological extremes in Canada, and performance comparison with classical models S. Latif & T. Ouarda https://doi.org/10.1016/j.ejrh.2026.103265
2803. A new approximation of Fermi-Dirac integrals of order 1/2 for degenerate semiconductor devices A. AlQurashi & C. Selvakumar https://doi.org/10.1016/j.spmi.2018.03.072
2804. Predicting chaotic time series and replicating chaotic attractors based on two novel echo state network models Y. Li & Y. Li https://doi.org/10.1016/j.neucom.2022.03.054
2805. Urban Traffic Flow Forecast Based on FastGCRNN Y. Zhang et al. https://doi.org/10.1155/2020/8859538
2806. PBL parameterization schemes sensitivity analysis on WRF modeling of a tornadic event environment in Skala Lakonia in September 2015 M. Mylonas et al. https://doi.org/10.1016/j.atmosres.2017.11.023
2807. Real‐time biomechanics using the finite element method and machine learning: Review and perspective R. Phellan et al. https://doi.org/10.1002/mp.14602
2808. Membrane-type acoustic metamaterial using cork sheets and attached masses based on reused materials G. Ciaburro & G. Iannace https://doi.org/10.1016/j.apacoust.2021.108605
2809. Facade geometry generation from low-resolution aerial photographs for building energy modeling J. Cao et al. https://doi.org/10.1016/j.buildenv.2017.07.018
2810. Probability and Statistical Modeling: Ti-6Al-4V Produced via Directed Energy Deposition P. Collins & D. Harlow https://doi.org/10.1007/s11665-021-06062-y
2811. ST-3DGMR: Spatio-temporal 3D grouped multiscale ResNet network for region-based urban traffic flow prediction R. He et al. https://doi.org/10.1016/j.ins.2022.12.066
2812. Importance of specific substrate utilization by microbes in microbially enhanced coal-bed methane production: A modelling study S. Emmert et al. https://doi.org/10.1016/j.coal.2020.103567
2813. Assessment of evaluation methods using infiltration data measured in heterogeneous mountain soils L. Jačka et al. https://doi.org/10.1016/j.geoderma.2016.04.023
2814. Bifurcation Analysis Framework of Spiking Neuron Models Z. Li et al. https://doi.org/10.1109/TCSI.2026.3710811
2815. Low-quality multivariate spatio-temporal serial data preprocessing T. Yu et al. https://doi.org/10.1007/s10586-017-1453-8
2816. Solve differential equations via a hybrid method between homotopy analytical method and sine cosine optimization algorithm M. najeeb et al. https://doi.org/10.1088/1742-6596/1879/3/032048
2817. Assessment of regional and global climate models for the investigation of monsoon rainfall variability over the North‐West Himalayan region S. Kundu et al. https://doi.org/10.1002/joc.7491
2818. Improving Spatial Resolution of GRACE-Derived Water Storage Changes Based on Geographically Weighted Regression Downscaled Model Z. Chen et al. https://doi.org/10.1109/JSTARS.2023.3272916
2819. Ensemble Soft Computing Models for Prediction of Deflection of Steel–Concrete Composite Bridges M. Le et al. https://doi.org/10.1007/s13369-023-08474-5
2820. Fine-Grained Visual Aspects in Genre Prediction P. Mondal et al. https://doi.org/10.1109/TCSS.2025.3591607
2821. Machine-learning-guided phase identification and hardness prediction of Al-Co-Cr-Fe-Mn-Nb-Ni-V containing high entropy alloys R. Jain et al. https://doi.org/10.1016/j.jallcom.2023.170193
2822. The 2-layer elasto-visco-plastic rheological model for the material parameter identification of bone tissue extended by a damage law A. Reisinger et al. https://doi.org/10.1016/j.jmbbm.2023.106259
2823. Statistical downscaling of GRACE gravity satellite-derived groundwater level data M. Golmohamadi & G. Joodaki https://doi.org/10.52547/jgit.8.3.83
2824. Deep Learning-Based Simulation of Surface Suspended Sediment Concentration in the Yangtze Estuary during Typhoon In-Fa Z. Ren et al. https://doi.org/10.3390/w16010146
2825. Spatiotemporal Analysis of XCO2 and Its Relationship to Urban and Green Areas of China’s Major Southern Cities from Remote Sensing and WRF-Chem Modeling Data from 2010 to 2019 Z. Tan et al. https://doi.org/10.3390/geographies3020013
2826. Semi-MapGen: Translation of Remote Sensing Image Into Map via Semisupervised Adversarial Learning J. Song et al. https://doi.org/10.1109/TGRS.2023.3263897
2827. Improving vascular access creation among hemodialysis patients: An agent-based modeling and simulation approach S. Mousavi et al. https://doi.org/10.1016/j.artmed.2022.102253
2828. Analysis and Forecasting of Cryptocurrency Markets Using Bayesian and LSTM-Based Deep Learning Models B. Biki et al. https://doi.org/10.3390/informatics12030087
2829. Classification of Nationwide Meteorological Types Based on K-means Clustering and Analysis of Type-Specific Ozone Variation Factors S. Jung et al. https://doi.org/10.5572/KOSAE.2026.42.3.557
2830. A Domain-Guided Noise-Optimization-Based Inversion Method for Facial Image Manipulation N. Yang et al. https://doi.org/10.1109/TIP.2021.3089905
2831. Cyanobacteria Index as a Tool for the Satellite Detection of Cyanobacteria Blooms in the Baltic Sea M. Konik et al. https://doi.org/10.3390/rs15061601
2832. MAPLE: Mixed Path Calculation in Tile-Based 3D Maps M. Ozyurt et al. https://doi.org/10.1109/LCOMM.2019.2954397
2833. Statistical evaluation of multiple interpolation techniques for spatial mapping of highly variable geotechnical facets of soil in natural deposition Z. Ijaz et al. https://doi.org/10.1007/s12145-022-00924-2
2834. Short-term wind speed forecasting using an optimized three-phase convolutional neural network fused with bidirectional long short-term memory network model L. Joseph et al. https://doi.org/10.1016/j.apenergy.2024.122624
2835. A Hybrid Machine Learning Model for Modeling Nitrate Concentration in Water Sources A. Mazraeh et al. https://doi.org/10.1007/s11270-023-06745-3
2836. Investigation of Prediction Accuracy of Hierarchical Linear Modelling and Artificial Neural Networks Methods on PISA 2018 Reading Literacy E. Akdoğdu Yıldız & K. Atalay Kabasakal https://doi.org/10.17152/gefad.1700937
2837. Unsupervised geomechanical state reconstruction in deviated wellbore using a hybrid Transformer graph attention deep learning architecture N. Kumar B & A. M https://doi.org/10.3389/fbuil.2026.1976552
2838. Direct Prediction of the Toxic Gas Diffusion Rule in a Real Environment Based on LSTM F. Qian et al. https://doi.org/10.3390/ijerph16122133
2839. Landuse/landcover monitoring and spatiotemporal modelling using multilayer perceptron and ‘multilayer perceptron’-Markov Chain ensemble models: A case study of Dausa City, Rajasthan S. Soni et al. https://doi.org/10.1088/1755-1315/1032/1/012028
2840. MAFA-Uformer: Multi-attention and dual-branch feature aggregation U-shaped transformer for sparse-view CT reconstruction X. Zhang et al. https://doi.org/10.1177/08953996241300016
2841. Research on Gating Fusion Algorithm for Power Grid Survey Data Based on Enhanced Mamba Spatial Neighborhood Relationship A. Zhang et al. https://doi.org/10.3390/s24216980
2842. Predictive Modeling of Heart Rate Dynamics based on Physical Characteristics and Exercise Parameters: A Machine Learning Approach M. Ali et al. https://doi.org/10.54392/ijpefs2421
2843. Bias correction of daily precipitation over South Korea from the long-term reanalysis using a composite Gamma-Pareto distribution approach D. Kim et al. https://doi.org/10.2166/nh.2019.127
2844. Vehicle Delay Model for Signalized Midblock Crosswalk Under Mixed Traffic Conditions S. Manthirikul & U. Jain https://doi.org/10.1177/03611981241236784
2845. Machine learning prediction of biochar yield based on different classification methods C. Zhao et al. https://doi.org/10.1063/5.0277427
2846. Evaluation of Trimble Centerpoint RTX correction service for real-time GNSS monitoring: a field-based comparison with RTK positioning G. Cecere et al. https://doi.org/10.1007/s42452-025-07889-z
2847. Computational Fluid Dynamics Modeling and Analysis of Lime Slurry Drying in a Laboratory Spray Dry Scrubber L. Lerotholi et al. https://doi.org/10.1021/acs.iecr.4c02014
2848. Evaluation of the Hydraulic Performance of the Drip Irrigation System Using IRRICAD at the University of Sulaimani B. Mohammed et al. https://doi.org/10.1061/JIDEDH.IRENG-10695
2849. Applicability of surrogate models for static displacement responses of transmission tower-line systems under different wind-profile parameter spaces J. Xu et al. https://doi.org/10.1016/j.rese.2026.08.001
2850. Estimation of Spectral Emissivity and S/Cu Ratio From Emissions of Copper Concentrates at the Flash Smelting Process M. Marin et al. https://doi.org/10.1109/ACCESS.2019.2925734
2851. An Improved Ocean Surface Albedo Computational Scheme: Structure and Performance J. Wei et al. https://doi.org/10.1029/2020JC016958
2852. Computational fluid dynamics modelling of hydrocarbon fires in open environments: Literature review A. Palacios et al. https://doi.org/10.1002/cjce.23768
2853. Evolutionary optimization for neural network-based discrete choice modeling: enhancing stability and efficiency H. Hasanzadeh et al. https://doi.org/10.1007/s11116-025-10682-x
2854. Improvement and application of the PCPF‐1@SWAT2012 model for predicting pesticide transport: a case study of the Sakura River watershed L. Tu et al. https://doi.org/10.1002/ps.4934
2855. South African Life Sciences teachers’ pedagogical beliefs and their influence on information communication and technology integration U. Ramnarain et al. https://doi.org/10.3389/feduc.2023.1217826
2856. Wireless channel estimation in OFDM systems based on collaborative filtering techniques V. Švedek et al. https://doi.org/10.2478/jee-2019-0033
2857. Assessment of CMIP6 model performance in simulating atmospheric aerosol and precipitation over Africa B. Mmame et al. https://doi.org/10.1016/j.asr.2023.06.030
2858. Heterogeneous radiotherapy dose-outcomes response in parotid glands H. Clark et al. https://doi.org/10.1088/2057-1739/aac8ea
2859. From ERA-Interim to ERA5: the considerable impact of ECMWF's next-generation reanalysis on Lagrangian transport simulations L. Hoffmann et al. https://doi.org/10.5194/acp-19-3097-2019
2860. Modeling of ethanol fermentation from carob extract–based medium by using Saccharomyces cerevisiae in the immobilized-cell stirred tank bioreactor E. Yatmaz et al. https://doi.org/10.1007/s13399-020-01154-6
2861. Soil mineralogical attributes estimated by color as accessed by proximal sensors and machine learning D. Baldo et al. https://doi.org/10.1002/saj2.20309
2862. A survey on missing data in machine learning T. Emmanuel et al. https://doi.org/10.1186/s40537-021-00516-9
2863. Machine Learning Models for Predicting the Compressive Strength of Concrete with Shredded PET Bottles and M-Sand as Fine Aggregate A. Nadimalla et al. https://doi.org/10.31436/iiumej.v26i1.2998
2864. Quality-Guaranteed and Cost-Effective Population Health Profiling: A Deep Active Learning Approach L. Chen et al. https://doi.org/10.1145/3617179
2865. Gully erosion susceptibility prediction in Mollisols using machine learning models Y. Wang et al. https://doi.org/10.2489/jswc.2023.00019
2866. RapidEELS: machine learning for denoising and classification in rapid acquisition electron energy loss spectroscopy C. Pate et al. https://doi.org/10.1038/s41598-021-97668-8
2867. Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images C. Fernández et al. https://doi.org/10.3390/rs13030396
2868. Meteorological influence on forecasting urban pollutants: Long-term predictability versus extreme events in a spatially heterogeneous urban ecosystem G. Ulpiani et al. https://doi.org/10.1016/j.scitotenv.2021.152537
2869. Predicting Regional Outbreaks of Hepatitis A Using 3D LSTM and Open Data in Korea K. Lee et al. https://doi.org/10.3390/electronics10212668
2870. RETRACTED ARTICLE: Imputation of missing precipitation data using KNN, SOM, RF, and FNN A. Sahoo & D. Ghose https://doi.org/10.1007/s00500-022-07029-4
2871. Symbolic regression-aided hyperparameter relationship for developing ANN for fragility prediction M. Parvizi et al. https://doi.org/10.1016/j.asoc.2025.113485
2872. Optimizing Sensor Placement and Wavelength Selection for Head-Mounted Photoplethysmography in Wearable Applications A. Alshehhi et al. https://doi.org/10.1109/JSEN.2026.3720430
2873. Temperature: A key parameter on soil content reduction simulation in recycled asphalt aggregate M. Borges Cabrera et al. https://doi.org/10.1016/j.jclepro.2020.121236
2874. Case study of the prediction of elective surgery durations in a New Zealand teaching hospital K. Soh et al. https://doi.org/10.1002/hpm.3046
2875. Analysis of sampling precision in low-density weed populations P. Hamouz & K. Hamouzová https://doi.org/10.1007/s11119-021-09851-6
2876. Spatiotemporal SWMM-LSTM surrogate modeling for efficient node-level water depth and inflow prediction in urban drainage networks N. Zafarmomen et al. https://doi.org/10.1017/wat.2026.10013
2877. Hydrodynamic and ecological 3D modeling in tropical lakes L. Amorim et al. https://doi.org/10.1007/s42452-021-04272-6
2878. Assessment of aerosol optical properties using remote sensing over highly urbanised twin cities of Pakistan M. Awais et al. https://doi.org/10.1016/j.jastp.2018.04.008
2879. Performance degradation trend prediction of proton exchange membrane fuel cell based on GA-TCN Z. Zhao et al. https://doi.org/10.1088/1361-6501/ad3ea4
2880. Design and Evaluation of Multi-Agent Architectures for Stock Price Prediction: A Vietnam Case Study D. Nguyen Minh & D. Huu https://doi.org/10.1109/ACCESS.2026.3704951
2881. Combined pharmacophore modeling, 3D-QSAR and docking studies to identify novel HDAC inhibitors using drug repurposing J. Liu et al. https://doi.org/10.1080/07391102.2019.1590241
2882. Intelligent Detection of Cognitive Stress in Subway Train Operators Using Multimodal Electrophysiological and Behavioral Signals X. Yang & L. Yu https://doi.org/10.3390/sym17081298
2883. Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans V. Juneja et al. https://doi.org/10.4315/0362-028X.JFP-17-391
2884. A Scenario-Based Model Comparison for Short-Term Day-Ahead Electricity Prices in Times of Economic and Political Tension D. Baskan et al. https://doi.org/10.3390/a16040177
2885. Forecasting monthly rainfall and temperature patterns in Van Province, Türkiye, using ARIMA and SARIMA models: a long-term climate analysis V. Yavuz https://doi.org/10.2166/wcc.2025.798
2886. Real-time earthquake magnitude estimation via a deep learning network based on waveform and text mixed modal B. Hou et al. https://doi.org/10.1186/s40623-024-02005-8
2887. Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials M. İnce & H. Varol Özkavak https://doi.org/10.3390/app15147997
2888. Strength of a cement-improved clay and a machine learning evaluation of interactions between observed mechanical behaviours H. Shiferaw et al. https://doi.org/10.1016/j.gsf.2026.102293
2889. Using Machine Learning Algorithms to Forecast the Sap Flow of Cherry Tomatoes in a Greenhouse A. Amir et al. https://doi.org/10.1109/ACCESS.2021.3127453
2890. Riesz fractional order derivative in Fractional Fourier Transform domain: An insight K. Kaur et al. https://doi.org/10.1016/j.dsp.2019.07.007
2891. Molecular pretraining models towards molecular property prediction J. Qiao et al. https://doi.org/10.1007/s11432-024-4457-2
2892. Nominal elastic modulus assessment in 3D-printed components under varying printing parameters using Bayesian methods and random forest surrogate modeling J. Zhang et al. https://doi.org/10.1371/journal.pone.0338204
2893. Influence of water quality, local knowledge and river–floodplain connectivity on commercial wild crayfish harvesting in the Atchafalaya River Basin I. Vargas‐Lopez et al. https://doi.org/10.1111/fme.12422
2894. EVDHM-ARIMA-Based Time Series Forecasting Model and Its Application for COVID-19 Cases R. Sharma et al. https://doi.org/10.1109/TIM.2020.3041833
2895. Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors Z. Yang & W. Gao https://doi.org/10.1002/advs.202106043
2896. Estimating GDP by Fusing Nighttime Light and Land Cover Data N. Xu et al. https://doi.org/10.1080/07038992.2024.2377641
2897. A maintenance-aware machine learning framework for network-level highway pavement condition prediction J. Kim et al. https://doi.org/10.1016/j.cacaie.2026.100091
2898. Hybrid Fuzzy Expert System and Difference Equation Software Filter for Biomedical Sensors A. Golcuk https://doi.org/10.1109/TIM.2022.3197803
2899. Prognostication of Shortwave Radiation Using an Improved No-Tuned Fast Machine Learning I. Ebtehaj et al. https://doi.org/10.3390/su13148009
2900. Considering spatial heterogeneity in modeling taxi speeding frequency: An advanced geographically weighted negative binomial regression approach L. Qu et al. https://doi.org/10.1016/j.aap.2025.108356
2901. Extracting High-Precision Vehicle Motion Data from Unmanned Aerial Vehicle Video Captured under Various Weather Conditions X. Li & J. Wu https://doi.org/10.3390/rs14215513
2902. Assessing safety at work using an adaptive neuro-fuzzy inference system (ANFIS) approach aided by partial least squares structural equation modeling (PLS-SEM) E. Çakıt et al. https://doi.org/10.1016/j.ergon.2020.102925
2903. Prediction of pasture yield using machine learning-based optical sensing: a systematic review C. Stumpe et al. https://doi.org/10.1007/s11119-023-10079-9
2904. Room-temperature and temperature-dependent QSRR modelling for predicting the nitrate radical reaction rate constants of organic chemicals using ensemble learning methods S. Gupta et al. https://doi.org/10.1080/1062936X.2016.1199592
2905. Prediction of cardiac disease-causing pattern using multimedia extraction in health ontology H. Yoo et al. https://doi.org/10.1007/s11042-020-09052-9
2906. TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms M. Patrick et al. https://doi.org/10.1051/matecconf/20178701006
2907. Field-Validated Accelerometer-Based Tension Estimation for Overhead Distribution Lines J. Kim https://doi.org/10.1109/TPWRD.2026.3697749
2908. Monte Carlo Simulations as a Decision Support to Interpret δ15N Values of Nitrate in Groundwater L. Wild et al. https://doi.org/10.1111/gwat.12936
2909. Unraveling the enrichment mechanism of indium in sphalerite: Insights from causal machine learning and global geochemical data X. Zhao et al. https://doi.org/10.1016/j.chemgeo.2026.123696
2910. A Machine Learning approach to reconstruct cloudy affected vegetation indices imagery via data fusion from Sentinel-1 and Landsat 8 E. dos Santos et al. https://doi.org/10.1016/j.compag.2022.106753
2911. Prediction of heat of hydration of cementitious systems using Gaussian process regression enables mass concrete thermal modeling L. Al-Hasani et al. https://doi.org/10.1617/s11527-023-02134-8
2912. The Tibetan Plateau’s Looming Trade-Off Attribution and Future Trajectories of Vegetation Growth Versus Water Yield R. Kong et al. https://doi.org/10.3390/f17020181
2913. Wind speed prediction method using Shared Weight Long Short-Term Memory Network and Gaussian Process Regression Z. Zhang et al. https://doi.org/10.1016/j.apenergy.2019.04.047
2914. Machine Learning Approach to Predict the Surface Charge Density of Monodispersed Particles in Gas–Solid Fluidized Beds J. Lu et al. https://doi.org/10.1021/acsomega.2c00299
2915. Numerical and Experimental Study on the Heat Dissipation Performance of a Novel System C. Yu et al. https://doi.org/10.3390/en13010106
2916. Bidirectional long short-term memory attention neural network to estimate neural mass model parameters H. Zhang et al. https://doi.org/10.1016/j.chaos.2025.116051
2917. Forest optimal rotation and valuation under different stochastic prices Z. Yu et al. https://doi.org/10.1007/s10342-025-01847-5
2918. Hemispheric lateralization of language processing: insights from network-based symptom mapping and patient subgroups Z. Dai et al. https://doi.org/10.1093/cercor/bhad437
2919. Ensemble machine learning framework for predicting and optimizing electromagnetic shielding of Al 6061 hybrid metal matrix composites C. Himagireesh et al. https://doi.org/10.1088/2631-8695/ae6050
2920. Modeling the neuro-mechanics of human balance when recovering from a fall: a continuous-time approach A. Cerda-Lugo et al. https://doi.org/10.1186/s12938-020-00811-1
2921. Hydromorphodynamics modeling of dredging and dumping activities in Mirim lagoon, RS, Brazil A. Bendô et al. https://doi.org/10.1016/j.oceaneng.2023.116219
2922. A physics-guided multi-task framework for joint forecasting of heating load and return temperatures at building-side district heating substations Z. Zhang et al. https://doi.org/10.1016/j.buildenv.2026.115090
2923. Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity A. Masrur Ahmed et al. https://doi.org/10.1016/j.jhydrol.2021.126350
2924. Application of supervised machine learning for predicting and classifying the lithology type of reservoir rock: the case study of Iraq M. Mohammedawi et al. https://doi.org/10.1007/s13202-026-02182-0
2925. Soil water content prediction across seasons using random forest based on precipitation-related data P. Chen et al. https://doi.org/10.1016/j.compag.2024.109802
2926. Future precipitation patterns: investigating the IDF curve shifts under CMIP6 pathways M. Khan et al. https://doi.org/10.2166/hydro.2025.092
2927. Coupling linear spectral unmixing and RUSLE2 to model soil erosion in the Boubo coastal watershed, Côte d'Ivoire L. Coulibaly et al. https://doi.org/10.1016/j.ecolind.2021.108092
2928. Predictive skill of extended range forecast of 2020–21 winter precipitation over North India M. Thayyil Mandodi & D. Pattanaik https://doi.org/10.1007/s00703-023-00965-2
2929. A radiative cooling enhanced liquid desiccant-based atmospheric water harvesting device F. Xiao et al. https://doi.org/10.1016/j.energy.2026.140730
2930. An updated version of the SZ-plugin: From space to space–time data-driven modeling in QGIS G. Titti et al. https://doi.org/10.1016/j.jag.2025.104679
2931. Coupling SWAT and LSTM models for enhanced daily phosphorus concentration forecasting in data-scarce watersheds X. Xi et al. https://doi.org/10.1016/j.jece.2026.121051
2932. Foreign arrivals nowcasting in Italy with Google Trends data F. Antolini & L. Grassini https://doi.org/10.1007/s11135-018-0748-z
2933. CECF-Net: Imputation of missing values in carbon flux time series via context enhancement and cross-scale fusion G. Wang et al. https://doi.org/10.1016/j.asoc.2026.115438
2934. Influent Forecasting for Wastewater Treatment Plants in North America G. Boyd et al. https://doi.org/10.3390/su11061764
2935. Crop Photosynthetic Performance Monitoring Based on a Combined System of Measured and Modelled Chloroplast Electron Transport Rate in Greenhouse Tomato W. Yu et al. https://doi.org/10.3389/fpls.2020.01038
2936. Evaluation of the CALIPSO Lidar-observed particulate backscattering coefficient on different spatiotemporal matchup scales M. Sun et al. https://doi.org/10.3389/fmars.2023.1181268
2937. Compressive strength detection of tunnel lining using hyperspectral images and machine learning H. Huang et al. https://doi.org/10.1016/j.tust.2024.105979
2938. Study of the distribution of lead (Pb) on mangrove roots (Rhizophora mucronata) and the utilization of mangrove roots as solid fuel Y. Kurniati et al. https://doi.org/10.1088/1755-1315/969/1/012007
2939. Assessment of critical parameters for artificial neural networks based short-term wind generation forecasting V. Sewdien et al. https://doi.org/10.1016/j.renene.2020.07.117
2940. Interlaboratory comparison of femur surface reconstruction from CT data compared to reference optical 3D scan E. Soodmand et al. https://doi.org/10.1186/s12938-018-0461-0
2941. Hybrid machine learning model for prediction of vertical deflection of composite bridges H. Ha et al. https://doi.org/10.1680/jbren.23.00007
2942. Assessment of a Fine-Tuned Vision-Language-Action Model for Robotic Feature-Following Inspection M. Krüger et al. https://doi.org/10.1007/s11063-026-11860-3
2943. HoloIntelligent: A Deep Learning Framework for Comparative Analysis of Holographic and Bright‐Field Imaging in Head and Neck Carcinoma Classification A. Nazir et al. https://doi.org/10.1111/coin.70280
2944. Machine learning-driven prediction of specific capacitance and specific energy in biochar-based supercapacitors X. Liu et al. https://doi.org/10.1016/j.jpowsour.2026.240247
2945. Time-Series Growth Prediction Model Based on U-Net and Machine Learning in Arabidopsis S. Chang et al. https://doi.org/10.3389/fpls.2021.721512
2946. New model averaging approach in predicting mortality rate of intensive care unit patients S. Mohd Padzil et al. https://doi.org/10.1088/1742-6596/1366/1/012123
2947. Forecasting Bitcoin Prices Using Deep Learning for Consumer-Centric Industrial Applications P. Roy et al. https://doi.org/10.1109/TCE.2023.3321653
2948. Thermal improvement of urban squares under spatial and functional constraints C. Wang et al. https://doi.org/10.1016/j.buildenv.2026.115053
2949. Real-Time Implicit Inverse Force Identification using Multi-Parameter Tikhonov Regularization to Attenuate Solution Error Propagation H. Baek et al. https://doi.org/10.1007/s42417-026-02776-2
2950. Research of low-cost air quality monitoring models with different machine learning algorithms G. Wang et al. https://doi.org/10.5194/amt-17-181-2024
2951. A comparative performance assessment of deep learning and shallow regression for bivariate indoor temperature forecasting M. Ennejjar et al. https://doi.org/10.1088/2631-8695/ae2c43
2952. 基于注意力状态空间模型与多频特征增强的全色锐化方法 李. Li Zhiqian et al. https://doi.org/10.3788/AOS251395
2953. Predicting environmental pollutants in the apartment public space: Evaluating the impact of spatial enclosure and monitoring locations Y. Lv et al. https://doi.org/10.1016/j.uclim.2024.102277
2954. Performance assessment of a predictive microbiology framework for Listeria monocytogenes growth in dry-cured fish F. Tomasello et al. https://doi.org/10.1016/j.foodcont.2026.111967
2955. CCR: Facial Image Editing with Continuity, Consistency and Reversibility N. Yang et al. https://doi.org/10.1007/s11263-023-01938-z
2956. Extreme Atlantic Hurricane Probability of Occurrence Through the Metastatistical Extreme Value Distribution S. Hosseini et al. https://doi.org/10.1029/2019GL086138
2957. Flood susceptibility mapping in an arid region of Pakistan through ensemble machine learning model A. Yaseen et al. https://doi.org/10.1007/s00477-022-02179-1
2958. Intra- and inter-rater reliability in log volume estimation based on LiDAR data and shape reconstruction algorithms: a case study on poplar logs G. Forkuo & S. Borz https://doi.org/10.3389/frsen.2025.1506838
2959. Experimental optimization and thermodynamic performance analysis of a solar-driven vacuum desalination system using RSM–BBD and ANFIS W. Singmai et al. https://doi.org/10.1016/j.applthermaleng.2026.131337
2960. Exploitation of a New Short-Term Multimodel Photovoltaic Power Forecasting Method in the Very Short-Term Horizon to Derive a Multi-Time Scale Forecasting System E. Collino & D. Ronzio https://doi.org/10.3390/en14030789
2961. 2019nCoVAS: Developing the Web Service for Epidemic Transmission Prediction, Genome Analysis, and Psychological Stress Assessment for 2019-nCoV M. Xiao et al. https://doi.org/10.1109/TCBB.2021.3049617
2962. Low-dose CT image denoising using residual convolutional network with fractional TV loss M. Chen et al. https://doi.org/10.1016/j.neucom.2020.10.004
2963. Forecasting PM10 and PM2.5 in the Aburrá Valley (Medellín, Colombia) via EnKF based data assimilation S. Lopez-Restrepo et al. https://doi.org/10.1016/j.atmosenv.2020.117507
2964. Nonintrusive Load Monitoring Using Recurrent Neural Networks with Occupants Location Information in Residential Buildings M. Lee & H. Moon https://doi.org/10.3390/en16093688
2965. Using multi-polarization C- and L-band synthetic aperture radar to estimate biomass and soil moisture of wheat fields M. Hosseini & H. McNairn https://doi.org/10.1016/j.jag.2017.01.006
2966. Combining Large Language Models with Satellite Embedding to Comprehensively Evaluate the Tibetan Plateau’s Ecological Quality Y. Yang et al. https://doi.org/10.3390/rs18040643
2967. Generation of tissues outside the field of view (FOV) of radiation therapy simulation imaging based on machine learning and patient body outline (PBO) S. Kim et al. https://doi.org/10.1186/s13014-023-02384-4
2968. A three-variables cokriging method to estimate bare-surface soil moisture using multi-temporal, VV-polarization synthetic-aperture radar data L. Zeng et al. https://doi.org/10.1007/s10040-020-02177-z
2969. Development of flow model for partly and fully saturated soils using water balance and water table depth fluctuation analysis Y. Zhu et al. https://doi.org/10.1016/j.jhydrol.2023.129259
2970. UdN: A Bio-Inspired Data Network for Significant Pattern Extraction in Cognitive Internet of Things V. Jha & P. Tripathi https://doi.org/10.1007/s43069-025-00492-3
2971. Comparative assessment of AI-based and classical DSAS approaches in multi-temporal shoreline prediction: A case study of Ras El-Bar coast, Egypt H. El-Asmar & M. Felfla https://doi.org/10.1016/j.isprsjprs.2026.01.040
2972. An Analysis of Disability Groupings and Transition Planning Experiences E. Davenport et al. https://doi.org/10.1177/00224669211024593
2973. Assessing the effectiveness of ensembles in Speech Emotion Recognition: Performance analysis under challenging scenarios J. López-Gil & N. Garay-Vitoria https://doi.org/10.1016/j.eswa.2023.122905
2974. Optimized machine learning models for predicting the tensile strength of high-performance concrete D. Kumar et al. https://doi.org/10.1080/24705314.2025.2471682
2975. Comparison of Five Different Lactation Curve Models to Estimate Milk Yield of Friesian Holstein Cows at BBPTU HPT Baturraden E. Nanda et al. https://doi.org/10.1088/1755-1315/334/1/012004
2976. In-pile heat conduction model of the dispersion nuclear fuel plate with particle agglomeration. Part II: Predicting the effective thermal conductivity under the in-pile thermal transfer pattern based on a deep neural network Y. Dong et al. https://doi.org/10.1016/j.jnucmat.2025.155692
2977. A systematic comparison of machine learning models for missing value imputation in household electricity consumption data B. Hanna et al. https://doi.org/10.1038/s41598-026-51159-w
2978. A Comparative Assessment of Conventional and Artificial Neural Networks Methods for Electricity Outage Forecasting A. Onaolapo et al. https://doi.org/10.3390/en15020511
2979. Comparative Study on the Different Downscaling Methods for GPM Products in Complex Terrain Areas J. Liu et al. https://doi.org/10.3390/earth6040129
2980. PPDIST, global 0.1° daily and 3-hourly precipitation probability distribution climatologies for 1979–2018 H. Beck et al. https://doi.org/10.1038/s41597-020-00631-x
2981. A network-based discrete choice model for decision-based design Z. Sha et al. https://doi.org/10.1017/dsj.2023.4
2982. Zone-specific prediction of specific charge in tunnel blasting with machine learning J. Kwon et al. https://doi.org/10.1016/j.kscej.2025.100478
2983. 基于自先验信息和TV约束的正交直线扫描CL图像重建 朱. ZHU Guorong et al. https://doi.org/10.3788/gzxb20245309.0910001
2984. Storm Time Total Electron Content Modeling Over African Low‐Latitude and Midlatitude Regions J. Uwamahoro et al. https://doi.org/10.1029/2018JA025455
2985. Towards the new generation of courtyard buildings as a healthy living concept for post-pandemic era P. Saadatjoo et al. https://doi.org/10.1016/j.scs.2023.104726
2986. EPOCH: enhanced procedure for operational change detection using historical invariant features and PCA guided multivariate statistical technique I. Misra et al. https://doi.org/10.1080/10106049.2021.2017018
2987. Cross-Corpus Readability Compatibility Assessment for English Texts Z. Li et al. https://doi.org/10.1109/ACCESS.2023.3315834
2988. Analysis of kinetic energy distribution of big gun sprinkler applied to continuous moving hose-drawn traveler M. Ge et al. https://doi.org/10.1016/j.agwat.2017.12.009
2989. Geostatistical Analysis and Delineation of Groundwater Potential Zones for Their Implications in Irrigated Agriculture of Punjab Pakistan A. Shakoor et al. https://doi.org/10.3390/world6030115
2990. A Novel Keep Zero as Zero Polar Correlation Technique for Mobile Robot Localization using LIDAR R. SIDHARTHAN et al. https://doi.org/10.4316/AECE.2016.04003
2991. Using deep learning approaches for coloring silicone maxillofacial prostheses: A comparison of two approaches M. Kurt et al. https://doi.org/10.4103/jips.jips_149_22
2992. Machine Learning-Based Prediction of Tribological Properties of Epoxy Composite Coating H. Yan et al. https://doi.org/10.3390/polym17030282
2993. Numerical Analysis of the Available Power in an Overtopping Wave Energy Converter Subjected to a Sea State of the Coastal Region of Tramandaí, Brazil L. Cisco et al. https://doi.org/10.3390/fluids7110359
2994. A Robust and Lightweight Loop Closure Detection Approach for Challenging Environments Y. Shi et al. https://doi.org/10.3390/drones8070322
2995. Ensemble Deep Learning for Global Solar Irradiance Forecasting in Egypt: A Multi-Model Approach H. Aboelkhair et al. https://doi.org/10.1007/s41748-026-01083-w
2996. Machine learning algorithm for the shear strength prediction of basalt-driven lateritic soil A. Niyogi et al. https://doi.org/10.1007/s12145-023-00950-8
2997. Design of phosphoryl containing podands with Li+/Na+ selectivity using machine learning V. Solov’ev et al. https://doi.org/10.1080/1062936X.2021.1929462
2998. Long-Term Electrical Load Forecasting in Rwanda Based on Support Vector Machine Enhanced with Q-SVM Optimization Kernel Function E. Uwimana et al. https://doi.org/10.4236/jpee.2023.118003
2999. Turbidity factor coefficient on the estimation of hourly solar radiation in Depok City, Indonesia M. Budiyanto et al. https://doi.org/10.1016/j.egyr.2019.11.152
3000. Modeling the Impact of Water Hyacinth on Evapotranspiration in the Chongón Reservoir Using Remote Sensing Techniques: Implications for Aquatic Ecology and Invasive Species Management C. Cárdenas-Cuadrado et al. https://doi.org/10.3390/hydrology12040080
3001. Lamb wave damage severity estimation using ensemble-based machine learning method with separate model network S. Rizvi & M. Abbas https://doi.org/10.1088/1361-665X/ac2e1a
3002. Transfer learning-based prediction of high-temperature fatigue life in Fe-based structural alloys with limited data Q. Wang et al. https://doi.org/10.20517/jmi.2026.06
3003. Using GPT-4o as a factor extractor for Brazilian consumer law judgments* L. Pereira et al. https://doi.org/10.1007/s10506-025-09466-6
3004. AutoML-Based Prediction of Process Outcomes in Expanded Polypropylene Autoclave Foaming E. Erkan https://doi.org/10.3390/machines14070797
3005. MSF-HierGNN: a multi-source substructure-fusion hierarchical GNN method and web server to predict molecular property for drug design M. Xiao et al. https://doi.org/10.1093/bib/bbag491
3006. The dynamics of burning activity on degraded peatland in two villages in Central Kalimantan, Indonesia S. Robb et al. https://doi.org/10.1071/WF22067
3007. Predicting Soil Properties Using Topographic and Climatic Variables İ. YENER et al. https://doi.org/10.17475/kastorman.1049347
3008. Co-Registration Methods and Error Analysis for Four Decades (1979–2018) of Glacier Elevation Changes in the Southern Patagonian Icefield P. Vacaflor et al. https://doi.org/10.3390/rs14040820
3009. How much is the view from the window worth? Machine learning-driven hedonic pricing model of the real estate market T. Potrawa & A. Tetereva https://doi.org/10.1016/j.jbusres.2022.01.027
3010. Prediction of Partition Coefficient of Carbamates using GA-MLR and GAANN Methods, and Comparison with Experimental Data S. Moosavi et al. https://doi.org/10.2174/1570178620666221205095036
3011. Development of Novel Oral Formulations of Disulfide Antioxidants Based on Porous Silica for Controlled Release of the Drugs E. Dolinina & E. Parfenyuk https://doi.org/10.3390/ma14040963
3012. A Multiscale Photovoltaic Power Forecasting Framework Using VMD and GRUFormer-Based Hybrid Deep Learning L. Xu et al. https://doi.org/10.1007/s40866-025-00299-5
3013. Forecasting Inflation From Disaggregated Data W. Martínez‐Rivera et al. https://doi.org/10.1002/asmb.70023
3014. Digital twins for monitoring and predicting the cooking of food products: A case study for a French crêpe I. Cabeza-Gil et al. https://doi.org/10.1016/j.jfoodeng.2023.111697
3015. Deep-learning-based cross-modality translation from Stokes image to bright-field contrast S. Wei et al. https://doi.org/10.1117/1.JBO.28.10.102911
3016. A hybrid machine learning model for predicting continuous cooling transformation diagrams in welding heat-affected zone of low alloy steels X. Geng et al. https://doi.org/10.1016/j.jmst.2021.07.038
3017. All optical third order tunable ordinary differential equation solutions based on double Sagnac rings coupled MZI on silicon waveguide chips M. Xu et al. https://doi.org/10.1117/1.JNP.17.046004
3018. Extreme pressure coefficients: modelling a hydraulic jump using deep-learning based methods S. Mousavi et al. https://doi.org/10.1007/s12046-024-02515-x
3019. A novel evapotranspiration based irrigation quantification method using the hydrological similar pixels algorithm J. Brombacher et al. https://doi.org/10.1016/j.agwat.2022.107602
3020. A new nonparametric copula framework for the joint analysis of river water temperature and low flow characteristics for aquatic habitat risk assessment S. Latif et al. https://doi.org/10.1016/j.jhydrol.2024.131079
3021. Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting M. Ali et al. https://doi.org/10.1016/j.compag.2018.07.013
3022. GIS-based spatial modeling of snow avalanches using four novel ensemble models P. Yariyan et al. https://doi.org/10.1016/j.scitotenv.2020.141008
3023. Analysis and Design Process for Predicting and Controlling Blood Glucose in Type 1 Diabetic Patients I. Gambo et al. https://doi.org/10.4018/IJHISI.289461
3024. Is the ISO 8996:2021 heart rate method accurate for predicting metabolic rate? An experimental validation based on Chinese young adults S. Gao et al. https://doi.org/10.1016/j.buildenv.2025.113235
3025. MOBİLYA SEKTÖRÜNDE SATIŞ TAHMİNİ: YİNELEMELİ SİNİR AĞI MODELLERİNİN KARŞILAŞTIRMALI ANALİZİ O. Şahin & B. Çubukçu https://doi.org/10.21923/jesd.1433624
3026. Modeling and Prediction of Near-Earth Plasma Sheet Parameters Using the Rice Convection Model and the Recurrent Neural Network S. Priyadarshi et al. https://doi.org/10.3389/fspas.2021.691000
3027. Using Analog Ensembles with Alternative Metrics for Hindcasting with Multistations C. Balsa et al. https://doi.org/10.55969/paradigmplus.v1n2a1
3028. Clinical validation of a deep-learning-based bone age software in healthy Korean children H. Nam et al. https://doi.org/10.6065/apem.2346050.025
3029. Nighttime lights analysis reveals disparate Covid-19 impacts in Uganda's refugee settlements H. Mizell & J. Van Den Hoek https://doi.org/10.1016/j.apgeog.2026.104192
3030. Prediction of Body Weight of a Person Lying on a Smart Mat in Nonrestraint and Unconsciousness Conditions T. Kim & Y. Hong https://doi.org/10.3390/s20123485
3031. Application of deep learning, machine learning and multi-criteria decision analysis for ecotourism potentiality assessment: a case study of the Sundarban Biosphere Reserve, India A. Baidya et al. https://doi.org/10.1007/s44163-025-00496-2
3032. Forecasting duration characteristics of near fault pulse-like ground motions using machine learning algorithms F. Wani et al. https://doi.org/10.1007/s00477-024-02729-9
3033. Mushroom cap phenotype extraction based on YOLOv11-SMD Y. Zhou et al. https://doi.org/10.1016/j.compag.2026.112402
3034. A Low-Cost IoT-Based Antenna Measurement System with Automated Dual-Axis Positioning and Mobile Data Visualization S. Phunklang et al. https://doi.org/10.3390/network6040090
3035. Interpretable machine learning framework for performance prediction and optimization of capacitive deionization Y. Wu et al. https://doi.org/10.1016/j.desal.2026.120468
3036. Power PV Forecasting using Machine Learning Algorithms Based on Weather Data in Semi-Arid Climate M. Boujoudar et al. https://doi.org/10.1051/bioconf/202410901024
3037. Quantifying pCO2 in biological ocean acidification experiments: A comparison of four methods S. Watson et al. https://doi.org/10.1371/journal.pone.0185469
3038. An Analysis of Biform Game Strategies for Supply Planning in a Full Distribution Network: Case of a Bottling Company M. Salma et al. https://doi.org/10.2139/ssrn.3186334
3039. Pulsed coaxial dielectric barrier discharge plasma loop-tubing system for inactivation of Escherichia coli K12 in glucose solution: Microbial and physicochemical kinetics and machine learning - Based predictive modeling P. Pichayamongkol et al. https://doi.org/10.1016/j.jfoodeng.2026.113154
3040. Modelling ionospheric phenomena and assessing the performance of IRI-Plas2017 during different phases of solar cycle 24 Y. Kayode et al. https://doi.org/10.15407/kfnt2025.02.047
3041. Switch from The Traditional RPLC Method to the Green RPLC Methods in The Determination of The Ionization Constant (pKa) of Favipiravir Y. Daldal https://doi.org/10.1002/slct.202402900
3042. Modelling the long‐term impact of harvest weed seed control for species like Bromus diandrus and Hordeum spp. that shed a portion of seed prior to harvest C. Borger et al. https://doi.org/10.1111/wre.12489
3043. Growth Effects as a Function of pH and Temperature of Salmonella enterica serovar Choleraesuis in In Vitro Tests and Chicken Meat: Prediction and Modeling M. Peruzzolo et al. https://doi.org/10.1007/s12088-023-01159-5
3044. Hydrodynamic Performance Assessment of Emerged, Alternatively Submerged and Submerged Semicircular Breakwater: An Experimental and Computational Study F. Al-Towayti et al. https://doi.org/10.3390/jmse12071105
3045. Development and validation of a framework for indoor thermal comfort in naturally ventilated university classrooms E. Kusi https://doi.org/10.1108/IJBPA-04-2025-0072
3046. EXPLORING THE ACCURACY AND RELIABILITY OF MACHINE LEARNING APPROACHES FOR STUDENT PERFORMANCE B. OWAIDAT https://doi.org/10.35784/acs-2024-29
3047. Improving 2D displacement accuracy in bridge vibration measurement with color space fusion and super resolution Q. He & S. Wang https://doi.org/10.1016/j.aei.2025.103248
3048. A k-d tree-based algorithm to parallelize Kriging interpolation of big spatial data H. Wei et al. https://doi.org/10.1080/15481603.2014.1002379
3049. Modeling the Photovoltaic Power Generation in Poland in the Light of PEP2040: An Application of Multiple Regression A. Rybak et al. https://doi.org/10.3390/en16227476
3050. Total Biomass in the Neotropical Savanna Domain: Stock Estimation and Modeling with Edaphic Variables K. Oliveira et al. https://doi.org/10.3390/plants15152261
3051. CNN-RNN architecture to calculate BPM from underwater ECG samples T. Beckingham et al. https://doi.org/10.1007/s10489-023-04522-7
3052. Measurements of wave damping by a grease ice slick in Svalbard using off-the-shelf sensors and open-source electronics J. RABAULT et al. https://doi.org/10.1017/jog.2017.1
3053. A Spectral Unmixing Method by Maximum Margin Criterion and Derivative Weights to Address Spectral Variability in Hyperspectral Imagery Y. Shao & J. Lan https://doi.org/10.3390/rs11091045
3054. A Robust and Efficient Loop Closure Detection Approach for Hybrid Ground/Aerial Vehicles Y. Wang et al. https://doi.org/10.3390/drones7020135
3055. A reaction-pathway-guided development of a kinetic mechanism for NO formation during N2O thermal decomposition S. Kim et al. https://doi.org/10.1016/j.csite.2026.108294
3056. Exploring the metabolic burden of surfactin biosynthesis and the metabolic costs of srfA operon expression in Bacillus subtilis E. Perino et al. https://doi.org/10.1186/s12934-026-03047-1
3057. Prediction of electrical energy consumption based on machine learning technique R. Banik et al. https://doi.org/10.1007/s00202-020-01126-z
3058. Mastering adverse weather: a two-stage approach for robust semantic segmentation in autonomous driving P. Liu et al. https://doi.org/10.1007/s00371-024-03663-1
3059. Phytoplankton Photophysiology Utilities: A Python Toolbox for the Standardization of Processing Active Chlorophyll-a Fluorescence Data T. Ryan-Keogh & C. Robinson https://doi.org/10.3389/fmars.2021.525414
3060. Morphology–aware spatiotemporal prediction of cumulonimbus–related radar echoes using CSDP–Net D. Wang et al. https://doi.org/10.1007/s00704-026-06276-x
3061. A time-domain method for load identification using moving weighted least square technique Y. Sun et al. https://doi.org/10.1016/j.compstruc.2020.106254
3062. Evaluating the Impact of Planetary Boundary Layer, Land Surface Model, and Microphysics Parameterization Schemes on Simulated GOES-16 Water Vapor Brightness Temperatures S. Griffin & J. Otkin https://doi.org/10.3390/atmos13030366
3063. Spatiotemporal Variation Assessment and Improved Prediction Of Cyanobacteria Blooms in Lakes Using Improved Machine Learning Model Based on Multivariate Data Y. Zhang et al. https://doi.org/10.1007/s00267-024-02108-8
3064. Local Indicators of Spatial Autocorrelation (LISA): Application to Blind Noise-Based Perceptual Quality Metric Index for Magnetic Resonance Images M. Osadebey et al. https://doi.org/10.3390/jimaging5010020
3065. Prediction of Surge Control Valve Opening for Centrifugal Compressors in Natural Gas Pipelines Based on GWO-Optimized BP Neural Network Q. Sun et al. https://doi.org/10.3390/a19040271
3066. Estimating mangrove aboveground biomass using Sentinel-2A Vegetation Indices in a tropical coastal ecosystem on the east coast of North Sumatra, Indonesia S. SAMSURI et al. https://doi.org/10.13057/asianjfor/r100131
3067. Response-calibrated SWAT process information for daily total nitrogen prediction in a gate-controlled shallow lake Y. Zou et al. https://doi.org/10.1007/s10661-026-16006-5
3068. Spectral density variation mapping of cerebral waves by three-dimensional interpolation techniques I. Nouira et al. https://doi.org/10.1002/ima.22136
3069. From lab to algorithm: a review of AI-driven predictive modeling in soil stabilization for road construction F. M’harzi Alaoui et al. https://doi.org/10.1007/s43995-026-00294-6
3070. Machine learning-based prediction of soil compaction parameters M. Senturk et al. https://doi.org/10.1007/s12665-025-12328-8
3071. Evaluation of the CORDEX regional climate models (RCMs) for simulating climate extremes in the Asian cities S. Neupane et al. https://doi.org/10.1016/j.scitotenv.2021.149137
3072. Two-set Variable Framework for Precise Vehicle Speed Prediction Y. Duan https://doi.org/10.1007/s13177-026-00696-9
3073. Weight-Constrained Neural Networks in Forecasting Tourist Volumes: A Case Study I. Livieris et al. https://doi.org/10.3390/electronics8091005
3074. Deep neural network-based optimal selection and blending ratio of waste seashells as an alternative to high-grade limestone depletion for SOX capture and utilization J. Lim et al. https://doi.org/10.1016/j.cej.2021.133244
3075. Prediction of true critical pressure of multi-component mixtures: Extending fast estimation methods H. Najafi et al. https://doi.org/10.1016/j.tca.2017.06.017
3076. Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm Z. Yaseen et al. https://doi.org/10.1088/1755-1315/143/1/012025
3077. Streamflow Prediction Using Deep Learning Neural Network: Case Study of Yangtze River D. Liu et al. https://doi.org/10.1109/ACCESS.2020.2993874
3078. High-frequency forecasting for grocery point-of-sales: intervention in practice and theoretical implications for operational design C. Dharmawardane et al. https://doi.org/10.1007/s12063-020-00176-7
3079. A new hybrid models based on the neural network and discrete wavelet transform to identify the CHIMERE model limitation A. Ajdour et al. https://doi.org/10.1007/s11356-022-23084-8
3080. FI-CRNet: Frequency Interaction for Cloud Removal in Remote Sensing Images P. Lei et al. https://doi.org/10.3390/rs18101608
3081. Interpretable probabilistic modeling method for runoff prediction: A case study in Yangtze River basin, China Q. Shen et al. https://doi.org/10.1016/j.ejrh.2024.101684
3082. The Effects of Increasing Ambient Temperature and Sea Surface Temperature Due to Global Warming on Combined Cycle Power Plant A. Aslan & A. Büyükköse https://doi.org/10.3390/su17104605
3083. Advanced techniques and applications of LiDAR place recognition in agricultural environments: A comprehensive survey J. Vilella-Cantos et al. https://doi.org/10.1016/j.neucom.2026.134497
3084. Physics-Informed Neural Network water surface predictability for 1D steady-state open channel cases with different flow types and complex bed profile shapes S. Cedillo et al. https://doi.org/10.1186/s40323-022-00226-8
3085. Enhancing PV system modeling accuracy with the irradiance intensity selection technique S. Songtrai et al. https://doi.org/10.35848/1347-4065/ae7269
3086. Evolutionary patterns and intelligent prediction of temperature fields in cold-region canal slopes H. Fang et al. https://doi.org/10.1007/s12145-026-02245-0
3087. Parameter reduction for PMV prediction via data driven approaches using the ASHRAE global thermal comfort database II and Chinese dataset A. Rahmanparast et al. https://doi.org/10.1016/j.applthermaleng.2025.127553
3088. Predictive machine learning optimization of anion exchange membrane water electrolysis systems M. Kabir et al. https://doi.org/10.1016/j.desal.2025.119198
3089. Mothers’ milk Na without Na:K ratio detects secretory activation in mothers of preterm infants Q. Pei et al. https://doi.org/10.1038/s41390-026-05206-x
3090. Pricing and reimbursement of generic pharmaceuticals in Turkey: Evaluation of hypertension drugs from 2007 to 2013 S. Kumru & M. Top https://doi.org/10.1016/j.hlpt.2018.03.004
3091. The Methodology Matters: What Influences Market Reaction, and Post-Issue Returns in Seasoned Equity Offerings? C. Krishnan & M. Wu https://doi.org/10.3390/jrfm15100473
3092. Fishery Sustainability and Climate Change Shocks in Gulf Cooperation Council Countries: Insights from a Panel VAR Model R. Elzaki https://doi.org/10.3390/fishes11070380
3093. Integrated Surface Water and Groundwater Modeling in Arid Environment, Al-Lusub Watershed, Saudi Arabia N. Al-Amri et al. https://doi.org/10.3390/w14193075
3094. Comparative Analysis of Model Evaluation Metrics in Energy Systems, Environmental Modeling, and Sustainability Science M. Mundu et al. https://doi.org/10.1155/er/6170467
3095. Design and performance investigation of heterojunction electrically doped junctionless TFET for label-free biomolecule detection considering ambipolar conduction P. Kwatra et al. https://doi.org/10.1016/j.micrna.2026.208564
3096. Fast three-dimensional NMR spectroscopy reconstruction based on Hankel matrix with two-directional sliding windows T. Qiu et al. https://doi.org/10.1016/j.mrl.2025.200254
3097. Adaptive variational fusion of multi-source lunar digital elevation models based on curvature regularization S. Qiu et al. https://doi.org/10.1016/j.cageo.2026.106107
3098. Impact of temperature and flow rate on oxygen dynamics and water quality in major Turkish rivers V. Yavuz https://doi.org/10.1038/s41598-025-06433-8
3099. Flood prediction with time series data mining: Systematic review D. Hakim et al. https://doi.org/10.1016/j.nhres.2023.10.001
3100. Gab-SSDS: An AI-Based Similar Days Selection Method for Load Forecast Z. Janković et al. https://doi.org/10.3389/fenrg.2022.844838
3101. Deep learning as a tool for ecology and evolution M. Borowiec et al. https://doi.org/10.1111/2041-210X.13901
3102. Constructing and Understanding Customer Spending Prediction Models T. Dang et al. https://doi.org/10.1007/s42979-023-02284-0
3103. A Systematic Review of Advances in Deep Learning Architectures for Efficient and Sustainable Photovoltaic Solar Tracking: Research Challenges and Future Directions A. Alhazmi et al. https://doi.org/10.3390/su17219625
3104. Machine Learning Models for Ecofriendly Optimum Design of Reinforced Concrete Columns Y. Aydın et al. https://doi.org/10.3390/app13074117
3105. FTnet: An integrated network for fusing multi-modal NDE data of lightning damage in aircraft composite materials Y. Fan et al. https://doi.org/10.1016/j.ndteint.2024.103196
3106. Multiple regression and group method of data handling-based models for predicting arsenic concentration in sedimentary phosphate rock M. Dassamiour et al. https://doi.org/10.1007/s13762-023-05452-0
3107. Forecasting short-term availability of bikes at sharing stations: a deep-learning approach G. Pallares et al. https://doi.org/10.1080/03081060.2026.2724315
3108. ANNs and game theory SHAP algorithms quantifying the contribution of geometric and temperature-dependent material properties to the thermal response of concrete walls exposed to elevated temperatures I. Bakas & K. Kontoleon https://doi.org/10.1016/j.conbuildmat.2025.143121
3109. Machine learning regression algorithms for predicting muscle, bone, carcass fat and commercial cuts in hairless lambs S. Monteiro et al. https://doi.org/10.1016/j.smallrumres.2024.107290
3110. Modelling Climate Change Impact on Irrigation Water Requirement and Yield of Winter Wheat (Triticum aestivum L.), Barley (Hordeum vulgare L.), and Fodder Maize (Zea mays L.) in the Semi-Arid Qazvin Plateau, Iran B. Mirgol et al. https://doi.org/10.3390/agriculture10030060
3111. Retail Demand Forecasting Using Spatial-Temporal Gradient Boosting Methods J. Wang et al. https://doi.org/10.1080/08874417.2023.2240753
3112. SpaNN: Spatial Transcriptomic Data Enhancement Using Deep Neural Network S. Chen et al. https://doi.org/10.1109/TCBBIO.2025.3594349
3113. Bridging climate and geophysical hazards: an integrated coastal hazard wheel and local disaster risk assessment framework for Weh Island, Indonesia M. Rauzan et al. https://doi.org/10.1007/s11069-026-08364-7
3114. The relationship between the golf swing plane and ball impact characteristics using trajectory ellipse fitting A. Morrison et al. https://doi.org/10.1080/02640414.2017.1303187
3115. Teaching Machine Learning Concepts to Engineers: A Practical Approach With Free Software A. de Sá Santos et al. https://doi.org/10.1002/cae.70239
3116. Processing of electrical resistivity tomography data using convolutional neural network in ERT-NET architectures P. Hiskiawan et al. https://doi.org/10.1007/s12517-023-11690-w
3117. Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy Z. Dong et al. https://doi.org/10.1016/j.compbiomed.2023.107073
3118. Estimación de la presión en atmósferas planetarias mediante gradientes de temperatura constante y lineal F. Rendón et al. https://doi.org/10.19136/jobs.a12n34.6685
3119. Artificial Intelligence and Extraction of Bioactive Compounds: The Case of Rosemary and Pressurized Liquid Extraction M. Mantiniotou et al. https://doi.org/10.3390/pr13061879
3120. Predicting reservoir temperature of geothermal systems in Western Anatolia, Turkey: A focus on predictive performance and explainability of machine learning models B. Ibrahim et al. https://doi.org/10.1016/j.geothermics.2023.102727
3121. Estimating daily ozone levels in urban ambient air D. Galán-Madruga et al. https://doi.org/10.1007/s10661-026-15566-w
3122. Comparison study of sampling methods for computer experiments using various performance measures I. Cho et al. https://doi.org/10.1007/s00158-016-1490-6
3123. On Solar Radiation Prediction for the East–Central European Region M. Mierzwiak et al. https://doi.org/10.3390/en15093153
3124. Investigating leadership discussion on social media: A NLP and machine learning perspective S. Shankar & V. Tewari https://doi.org/10.1016/j.techsoc.2025.102936
3125. Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities M. Thafar et al. https://doi.org/10.3389/fchem.2019.00782
3126. Machine learning algorithms predict bark coverages on saguaro cacti (Carnegiea gigantea) L. Evans et al. https://doi.org/10.1016/j.flora.2019.151527
3127. Modeling hourly air temperature based on internationally agreed times and the daily minimum temperature S. Radons et al. https://doi.org/10.1590/1807-1929/agriambi.v23n11p807-811
3128. Time-delayed machine learning models for estimating groundwater depth in the Hetao Irrigation District, China C. Ao et al. https://doi.org/10.1016/j.agwat.2021.107032
3129. Single-step synthesis of titanium nitride-oxide composite and AI-driven aging forecast for lithium–sulfur batteries K. Li et al. https://doi.org/10.1039/D4TA00234B
3130. Stochastic modeling method and elastic parameter analysis of the irregular columnar jointed rock masses considering the joint characteristics within the cross section H. Zhou et al. https://doi.org/10.1007/s12665-023-11364-6
3131. Feature-based lithium-ion battery state of health estimation with artificial neural networks L. Driscoll et al. https://doi.org/10.1016/j.est.2022.104584
3132. A Novel Strategy to Fit and Validate Physiological Models: A Case Study of a Cardiorespiratory Model for Simulation of Incremental Aerobic Exercise C. Sarmiento et al. https://doi.org/10.3390/diagnostics13050908
3133. Multi-Physics Field Computation for Microwave Heating of Multi-Mobile Components Based on Transformation Optics and Implicit Function H. Chen et al. https://doi.org/10.3390/app14010058
3134. FusionGP: Scalable Bayesian spatio-temporal fusion of satellite and ground observations for urban NO2 mapping G. Oduori et al. https://doi.org/10.1016/j.acags.2026.100416
3135. Comparison of different nonlinear models for degradability in situ dry matter of maize harvested at various maturity stages H. HIZLI & N. KILIÇALP https://doi.org/10.47495/okufbed.979558
3136. Comparison of Urban Heat Island Diurnal Cycles under Various Atmospheric Conditions Using WRF-UCM T. Fedor & J. Hofierka https://doi.org/10.3390/atmos13122057
3137. Effects of climate change on wet and dry spells in Kelantan River basin using physically-based hydrological model and CMIP6 scenarios N. Mohamad Arbai & M. Irie https://doi.org/10.1016/j.ejrh.2025.102219
3138. Performance Analysis of Model for Road Surface Temperature Change Pattern by Road Section J. Kim et al. https://doi.org/10.7855/IJHE.2018.20.5.121
3139. Can NMR spectroscopy discriminate between NPS amphetamines and cathinones? An evaluation by in silico studies and chemometrics C. Rodrigues et al. https://doi.org/10.1016/j.chemolab.2021.104265
3140. Improving the Detection Accuracy of Underwater Obstacles Based on a Novel Combined Method of Support Vector Regression and Gravity Gradient T. Fu et al. https://doi.org/10.3390/rs15082188
3141. CGAformer: Multi-scale feature Transformer with MLP architecture for short-term photovoltaic power forecasting R. Chen et al. https://doi.org/10.1016/j.energy.2024.133495
3142. A contactless measuring speed system of belt conveyor based on machine vision and machine learning Y. Gao et al. https://doi.org/10.1016/j.measurement.2019.03.030
3143. Eğirdir Gölü alansal değişiminin uzaktan algılama ve coğrafi bilgi sistemleri yardımıyla analizi M. Kale & M. Erişmiş https://doi.org/10.32003/igge.1380588
3144. Modelling the Influence of Inflation on Foreign Travel Dynamics: A Comparative Analysis of Linear and Machine Learning Models E. C. A. & A. C. O. https://doi.org/10.52589/JARMS-QEBGPVMW
3145. Monitoring Hospital Visitors Could Enhance the Prediction of the Plastic Waste Collection Demand and Its Management R. Cong et al. https://doi.org/10.3390/waste3030023
3146. Seismic Hazards Along the Longmen Shan Fault: Insights from Stress Transfer Between Major Earthquakes and Regional b-Values Y. Sun et al. https://doi.org/10.1007/s00024-023-03357-0
3147. Groundwater Prediction Using Machine-Learning Tools E. Hussein et al. https://doi.org/10.3390/a13110300
3148. Temporal flood forecasting for trans-boundary Jhelum River of Greater Himalayas S. Parvaze et al. https://doi.org/10.1007/s00704-021-03562-8
3149. Performance evaluation of regression models for COVID-19: A statistical and predictive perspective M. Khan et al. https://doi.org/10.1016/j.asej.2021.08.016
3150. ElectroPredictor: An Application to Predict Mayr’s Electrophilicity E through Implementation of an Ensemble Model Based on Machine Learning Algorithms S. Cuesta et al. https://doi.org/10.1021/acs.jcim.2c01367
3151. Borsa İstanbul’da Kote Bireysel Emeklilik, Hayat Ve Hayat-Dışı Sigorta Şirketlerinin Hisse Senedi Fiyat Tahmininde Box-Jenkıns Yöntemi F. Kurt & S. Senal https://doi.org/10.25095/mufad.465942
3152. Hydrological response to climate change in Baro basin, Ethiopia, using representative concentration pathway scenarios T. Ebissa et al. https://doi.org/10.1186/s40068-024-00370-7
3153. Integrating data-to-data correlation into inverse distance weighting Z. Li et al. https://doi.org/10.1007/s10596-019-09913-9
3154. Beyond prediction: integrating machine learning and structural modeling to explain student performance H. Wang et al. https://doi.org/10.1007/s12065-026-01192-5
3155. Assessing safety risks associated with Burkholderia gladiolus in soaked Auricularia auricula-judae: One instant predictive model study X. Chen et al. https://doi.org/10.1016/j.ijfoodmicro.2025.111212
3156. Vision-Based Measurement System for Automated Quality Inspection of CNC Turned Components A. Oviedo-Montaño et al. https://doi.org/10.3390/app162010161
3157. Appraising the effects of atmospheric aerosols and ground particulates concentrations on GPS-derived PWV estimates Y. Aliyu & J. Botai https://doi.org/10.1016/j.atmosenv.2018.09.001
3158. Enhancing predictive ability of optimized group method of data handling (GMDH) method for wildfire susceptibility mapping T. Tran et al. https://doi.org/10.1016/j.agrformet.2023.109587
3159. Jointly Modeling Spatio–Temporal Dependencies and Daily Flow Correlations for Crowd Flow Prediction T. Zang et al. https://doi.org/10.1145/3439346
3160. Improved Mass Accuracy and Isotope Confirmation through Alignment of Ultrahigh-Resolution Mass Spectra of Complex Natural Mixtures J. Merder et al. https://doi.org/10.1021/acs.analchem.9b04234
3161. Quantitative and qualitative evaluation on the accuracy of three intraoral scanners for human identification in forensic odontology E. Bae & E. Woo https://doi.org/10.5115/acb.21.136
3162. Predictive framework for detecting main bearing faults in direct-drive horizontal-axis wind turbines using supervisory control and data acquisition J. Liu et al. https://doi.org/10.1177/16878132261464392
3163. An Assessment of the Effectiveness of Tree-Based Models for Multi-Variate Flood Damage Assessment in Australia R. Hasanzadeh Nafari et al. https://doi.org/10.3390/w8070282
3164. Imputation by feature importance (IBFI): A methodology to envelop machine learning method for imputing missing patterns in time series data A. Mir et al. https://doi.org/10.1371/journal.pone.0262131
3165. SOSSF: Landsat-8 Image Synthesis on the Blending of Sentinel-1 and MODIS Data Y. Xia et al. https://doi.org/10.1109/TGRS.2024.3352662
3166. Mapping soil available copper content in the mine tailings pond with combined simulated annealing deep neural network and UAV hyperspectral images Y. Zhang et al. https://doi.org/10.1016/j.envpol.2022.120962
3167. Machine learning-based permeability prediction for CO₂ storage: A case study from the Petrel Sub-basin, Australia M. Waqar et al. https://doi.org/10.1016/j.gete.2026.100867
3168. An overview of performance evaluation metrics for short-term statistical wind power forecasting J. González-Sopeña et al. https://doi.org/10.1016/j.rser.2020.110515
3169. RTS-GAT: Spatial Graph Attention-Based Spatio-Temporal Flow Prediction for Big Data Retailing S. Luo https://doi.org/10.1109/ACCESS.2022.3230660
3170. Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies E. Chong et al. https://doi.org/10.1016/j.eswa.2017.04.030
3171. A Data-Driven Soft Sensor for Mass Flow Estimation S. Sobreira et al. https://doi.org/10.1109/TIM.2023.3273658
3172. Data-driven Root Tuber Biomass Estimation via a Wireless Network T. Wang et al. https://doi.org/10.1145/3800586
3173. A Historical Excursus on the Statistical Validation Parameters for QSAR Models: A Clarification Concerning Metrics and Terminology P. Gramatica & A. Sangion https://doi.org/10.1021/acs.jcim.6b00088
3174. High-Resolution Gridded Population Datasets: Exploring the Capabilities of the World Settlement Footprint 2019 Imperviousness Layer for the African Continent D. Palacios-Lopez et al. https://doi.org/10.3390/rs13061142
3175. Pointwise and Complex Quality Metrics in Atmospheric Modeling: Methods and Approaches V. Rezvov et al. https://doi.org/10.3103/S0027134924702229
3176. Explainable machine learning reveals diverse yield-determining factors among Thai rice farmer cohorts: Implications for targeted agricultural support M. Suriyalaksh et al. https://doi.org/10.1371/journal.pone.0349688
3177. Development of Parameter-Tuned Algorithms for Chlorophyll-a Concentration Estimates in the Southern Ocean M. Cha et al. https://doi.org/10.3390/rs17213595
3178. NDMI-Derived Field-Scale Soil Moisture Prediction Using ERA5 and LSTM for Precision Agriculture E. Koohikeradeh et al. https://doi.org/10.3390/su17062399
3179. An edge–cloud integrated framework for flexible and dynamic stream analytics X. Wang et al. https://doi.org/10.1016/j.future.2022.07.023
3180. Validation of the Effectiveness of Visual Feedback Systems in Respiratory Gating Carbon Ion Radiation Therapy R. Umetani et al. https://doi.org/10.1016/j.ijpt.2026.101319
3181. Effective cataract surgical coverage in adults aged 50 years and older: empirical estimates from population-based surveys in 68 countries and modelled estimates for 2000–30 I. McCormick et al. https://doi.org/10.1016/S2214-109X(25)00435-8
3182. Active temperature control of electric drivetrains for efficiency increase A. Wahl et al. https://doi.org/10.1016/j.apenergy.2023.120887
3183. Can high resolution UAV-derived weed maps replace camera-based targeted spray application? M. Adhikari et al. https://doi.org/10.3389/fagro.2026.1817915
3184. Artificial Neural Network Estimation of Sea Surface Temperature from Oceanographic Variables M. Umoh et al. https://doi.org/10.62292/njtep.v4i3.2026.171
3185. Evaluation of Four Methods for Predicting Carbon Stocks of Korean Pine Plantations in Heilongjiang Province, China H. Gao et al. https://doi.org/10.1371/journal.pone.0145017
3186. ePAMeT: evolving predictive associative memories for time series I. AbouHassan et al. https://doi.org/10.1007/s12530-024-09628-y
3187. A deep learning approach for assessing environmental stress dynamics in the Makkah watersheds, Saudi Arabia A. Al-Huqail & Z. Islam https://doi.org/10.3389/fenvs.2026.1723462
3188. Estimating Location-Adjustment Factors for Conceptual Cost Estimating Based on Nighttime Light Satellite Imagery S. Zhang et al. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001216
3189. A Comprehensive Case Study of Wind Energy Production Forecasting in Türkiye Using Enhanced Attention BiLSTM M. Çeçen et al. https://doi.org/10.1002/we.70114
3190. Assessing rating curve uncertainty T. McMahon et al. https://doi.org/10.1080/02626667.2024.2442736
3191. Estimation of nitrogen and phosphorus fluxes into a Barrier Island lagoon via meteoric groundwater discharge W. Al-Taliby & A. Pandit https://doi.org/10.1016/j.scitotenv.2023.163927
3192. Measuring Detection of Signature On Enterprise Computer Network S. Alviana & I. Sumitra https://doi.org/10.1088/1757-899X/662/5/052008
3193. An empirical-based rainfall-runoff modelling using optimization technique B. Roy & M. Singh https://doi.org/10.1080/15715124.2019.1680557
3194. A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms J. Lee et al. https://doi.org/10.1109/ACCESS.2025.3596531
3195. Deep Feature Selection of Meteorological Variables for LSTM-Based PV Power Forecasting in High-Dimensional Time-Series Data H. Mauladdawilah et al. https://doi.org/10.3390/a18080496
3196. Hybrid Convolutional Neural Network-Multilayer Perceptron Model for Solar Radiation Prediction S. Ghimire et al. https://doi.org/10.1007/s12559-022-10070-y
3197. Evaluation of different gridded precipitation products for drought monitoring: a case study of Central India M. Kesarwani et al. https://doi.org/10.1007/s00704-022-04304-0
3198. Long Short-Term Memory Based Subsurface Drainage Control for Rainfall-Induced Landslide Prevention A. Biniyaz et al. https://doi.org/10.3390/geosciences12020064
3199. Proceso operativo simple para el Análisis de Frecuencias de Crecientes con series de duración parcial D. Campos Aranda https://doi.org/10.24850/j-tyca-16-3-8
3200. Estimation of actual evapotranspiration and stage-wise crop coefficients for transplanted rice using a modified non-weighing paddy lysimeter and their prediction on machine ensemble approach in the middle Indo-Gangetic plains of South Asia A. Kumari et al. https://doi.org/10.1007/s10668-025-06878-x
3201. AutoReserve: A Web-Based Tool for Personal Auto Insurance Loss Reserving with Classical and Machine Learning Methods L. Xiong et al. https://doi.org/10.3390/risks11070131
3202. Development of a Numerical Prediction Model for Marine Lower Atmospheric Ducts and Its Evaluation across the South China Sea Q. Liu et al. https://doi.org/10.3390/jmse12010141
3203. Performance Evaluation of Machine Learning Models for Predicting Energy Consumption and Occupant Dissatisfaction in Buildings H. Hosamo & S. Mazzetto https://doi.org/10.3390/buildings15010039
3204. Assessment of droughts through SPEI and SPI indices in arid and semi-arid watersheds of San Luis Potosí, México V. Escamilla-Rivera et al. https://doi.org/10.24850/j-tyca-18-02-08
3205. Design and Comparison of Parallel Dynamic Matérn Kernel-Based Regression Models and Machine Learning Approaches: Application to Bias Correction in Numerical Weather Prediction V. Migallón et al. https://doi.org/10.1007/s42967-025-00490-6
3206. An AI-Empowered Framework for Cross-Layer Softwarized Infrastructure State Assessment A. Diamanti et al. https://doi.org/10.1109/TNSM.2022.3161872
3207. Spatiotemporal analysis and prediction of shoreline dynamics: A comparative study of machine learning and traditional forecasting approach R. Elboghdady et al. https://doi.org/10.1080/1064119X.2026.2626019
3208. Nitrogen dioxide (NO2) Meteorology and predictability for air quality management using TROPOMI P. Asilevi et al. https://doi.org/10.1038/s44407-024-00003-4
3209. A fuzzy model for generalized transportation problems in China M. Aljanabi et al. https://doi.org/10.1002/cpe.8126
3210. A reliability-based multidisciplinary design parallel optimization method based on double-layer approximation model for nuclear fuel assembly bottom nozzle C. Wan et al. https://doi.org/10.1016/j.pnucene.2024.105292
3211. Be aware of error measures. Further studies on validation of predictive QSAR models K. Roy et al. https://doi.org/10.1016/j.chemolab.2016.01.008
3212. Theoretical characterization of annular array as a volumetric optoacoustic ultrasound handheld probe M. Azizian Kalkhoran & D. Vray https://doi.org/10.1117/1.JBO.23.2.025004
3213. Dynamic selection of ensemble-based regression models: Systematic literature review H. Carvalho et al. https://doi.org/10.1016/j.eswa.2025.128429
3214. Smart Electricity Meter Load Prediction in Dubai Using MLR, ANN, RF, and ARIMA H. Sayed et al. https://doi.org/10.3390/electronics12020389
3215. Dual-View Prompting for Cloud Removal Y. Deng et al. https://doi.org/10.1109/TGRS.2025.3614865
3216. Reliability Assessment of Empirical Equations, ANN and MARS Models for Predicting the Mode I Fracture Toughness from Non-destructive Rock Properties A. Lawal & S. Kwon https://doi.org/10.1007/s00603-023-03345-9
3217. Numeric promoter description – A comparative view on concepts and general application R. Beier & D. Labudde https://doi.org/10.1016/j.jmgm.2015.11.011
3218. Drought Projections in the Northernmost Region of South America Under Different Climate Change Scenarios H. Arregocés et al. https://doi.org/10.3390/earth6040122
3219. Artificial Intelligence (AI) Use in Data Analysis: A Comparison of ChatGPT and SmartPLS Outputs in PLS-SEM Analysis Y. Toraman & O. Şimşek https://doi.org/10.2339/politeknik.1739414
3220. Assessment of IEC Normal Turbulence Model and Modelling of the Wind Turbulence Intensity for Small Wind Turbine Design in Tropical Area: Case of the Coastal Region of Benin H. Donnou et al. https://doi.org/10.14710/ijred.9.2.263-286
3221. Development and Evaluation of Predictive Machine Learning Models for Crude Oil Supply Chain Logistics in the USA M. Prah et al. https://doi.org/10.4236/ti.2025.162005
3222. Machine Learning Based Prediction of Nanoscale Ice Adhesion on Rough Surfaces S. Ringdahl et al. https://doi.org/10.3390/coatings11010033
3223. Quantitative assessment of spatiotemporal variability in air quality within the Amman-Zarqa urban Area, Jordan A. Al-Rawabdeh et al. https://doi.org/10.1016/j.ejrs.2025.06.002
3224. High-accuracy machine learning approach for predicting J–V characteristics of perovskite solar cells under variable irradiance A. Toprak https://doi.org/10.1038/s41598-025-25156-4
3225. Artificial intelligence algorithms to predict Italian real estate market prices L. Rampini & F. Re Cecconi https://doi.org/10.1108/JPIF-08-2021-0073
3226. Design of Low-Cost High Accuracy Motion Capture System D. Kızılöz & M. Peker https://doi.org/10.65520/erciyesfen.1968365
3227. How Connected Cars Could Capture Cloud Dynamics for Solar Forecasting—Evidence from Two Simulation Scenarios T. Veihelmann et al. https://doi.org/10.1002/solr.202400470
3228. Healthy area of the penultimate leaf (F2) as a predictor of barley grain yield under foliar disease pressure in semi-arid environments H. Wazziki & B. Yousfi https://doi.org/10.1007/s42976-026-00812-1
3229. Optimizing WRF Configurations for Improved Precipitation Forecasting in West Africa: Sensitivity to Cumulus and PBL Schemes in a Senegal Case Study A. Coly et al. https://doi.org/10.3390/cli13090181
3230. The Dynamic Behaviour of a Binary Adsorbent in a Fixed Bed Column for the Removal of Pb2+ Ions from Contaminated Water Bodies C. Harripersadth & P. Musonge https://doi.org/10.3390/su14137662
3231. Supervised learning-based artificial senses for non-destructive fish quality classification R. Saeed et al. https://doi.org/10.1016/j.bios.2024.116770
3232. Multi-Pattern Scanning Mamba for Cloud Removal X. Xin et al. https://doi.org/10.3390/rs17213593
3233. Single-Band NDVI Spatial Downscaling: Synthetic Benchmarking and Landsat-8/Sentinel-2 Cross-Sensor Evaluation S. Yu et al. https://doi.org/10.3390/s26206601
3234. A 3D vehicle-bridge interaction framework integrating energy-conserving Hamilton’s principle and stabilized Newmark-β method X. Yin et al. https://doi.org/10.1016/j.advengsoft.2025.104022
3235. Development of an AI image Recognition–based lateral flow immunochromatographic test strip for higenamine detection R. Zhang et al. https://doi.org/10.1016/j.ab.2026.116069
3236. New approach for regional water-energy-food nexus security assessment: Enhancing the random forest model with the aquila optimizer algorithm W. Ru et al. https://doi.org/10.1016/j.agwat.2024.108946
3237. Predicting tilling and seeding operation times in grain production: A comparison of machine learning and mechanistic models L. Scheurer et al. https://doi.org/10.1016/j.atech.2025.101043
3238. AI-Driven Stacking Ensemble for Predicting Total Power Output of Wave Energy Converters: A Data-Driven Approach to Renewable Energy Processes T. Muthamizhan et al. https://doi.org/10.3390/pr13040961
3239. Evaluation of pre-dilution combined with optical/fluorescent platelet counting for correcting pseudothrombocytopenia L. Xiong et al. https://doi.org/10.3389/fmed.2026.1855339
3240. Clustering-based spatial transfer learning for short-term ozone forecasting T. Deng et al. https://doi.org/10.1016/j.hazadv.2022.100168
3241. Dynamic detection of water surface area of Ebinur Lake using multi-source satellite data (Landsat and Sentinel-1A) and its responses to changing environment J. Wang et al. https://doi.org/10.1016/j.catena.2019.02.020
3242. CFD simulation advances in urban aerodynamics: Accuracy, validation, and high-rise building applications A. Idrissi et al. https://doi.org/10.1016/j.rineng.2025.105148
3243. DINI: data imputation using neural inversion for edge applications S. Tuli & N. Jha https://doi.org/10.1038/s41598-022-24369-1
3244. Statistical Evaluation and Synthetic Generation of Ultra-Wideband Distance Measurements for Indoor Positioning Systems P. Schwarzbach et al. https://doi.org/10.1109/JSEN.2021.3121627
3245. Relative Radiometric Normalization for the PlanetScope Nanosatellite Constellation Based on Sentinel-2 Images R. Dias et al. https://doi.org/10.3390/rs16214047
3246. Deep learning-driven statistical bias correction for climate risk assessment of projected temperature extremes in the Nordic region P. Loganathan et al. https://doi.org/10.1038/s44304-026-00207-6
3247. Accurate solar radiation site adaptation: Harnessing satellite data and in situ measurements J. Ruiz-Munoz & L. Hoyos-Gómez https://doi.org/10.1063/5.0226782
3248. AI-based spatial prediction of mangrove soil organic carbon and blue-carbon storage for sustainable tropical coastal wetlands I. Mondal et al. https://doi.org/10.1016/j.ecohyd.2026.100814
3249. Estimation of Soil Salinization by Machine Learning Algorithms in Different Arid Regions of Northwest China X. Jiang et al. https://doi.org/10.3390/rs14020347
3250. Uncertainty of Rainfall Products: Impact on Modelling Household Nutrition from Rain-Fed Agriculture in Southern Africa R. Luetkemeier et al. https://doi.org/10.3390/w10040499
3251. AI-Based Model Order Reduction Techniques: A Survey S. Mallick & M. Mittal https://doi.org/10.1007/s11831-024-10207-2
3252. Remote sensing vegetation Indices-Driven models for sugarcane evapotranspiration estimation in the semiarid Ethiopian Rift Valley G. W. Woldemariam et al. https://doi.org/10.1016/j.isprsjprs.2024.07.004
3253. A hybrid PCA-LSTM predictive approach for enhancing multi-step indoor temperature prediction towards energy-efficient HVAC control M. Ennejjar et al. https://doi.org/10.1088/1402-4896/adcc67
3254. Simulation Analysis of Magnetic Gradient Full-Tensor Measurement System L. Xu et al. https://doi.org/10.1155/2021/6688364
3255. Forecasting nonperforming loans using machine learning M. Abdullah et al. https://doi.org/10.1002/for.2977
3256. Machine learning-based prediction of proton-induced reaction cross-sections for medically relevant bromine radioisotopes P. Khalilzadeh et al. https://doi.org/10.1016/j.rinp.2025.108357
3257. Characterization of a Spiking Convolutional Processor for FPGA D. Curra-Sosa et al. https://doi.org/10.3390/s26061801
3258. Source Apportionment of Heavy Metal Contamination in Urban-Agricultural-Aquacultural Soils near the Bohai Bay Coast, Using Land-Use Classification and Google Satellite Tracing L. Zeng et al. https://doi.org/10.3390/rs14102436
3259. A Hybrid Approach to Evaluate Business Efficiency, Profitability, and Market Valuation: An Empirical Validation Y. Liao et al. https://doi.org/10.12688/f1000research.178626.1
3260. Inter-moieties reactivity correlations: an approach to estimate the reactivity endpoints of major atmospheric reactants towards organic chemicals S. Gupta et al. https://doi.org/10.1039/C6RA06805G
3261. Harnessing artificial neural networks for coastal erosion prediction: A systematic review A. Khan et al. https://doi.org/10.1016/j.marpol.2025.106704
3262. Reshaping Industrial Maintenance with Machine Learning: Fouling Control Using Optimized Gaussian Process Regression F. Negri et al. https://doi.org/10.1021/acs.iecr.4c04550
3263. Impact of Domain Nesting on High-Resolution Forecasts of Solar Conditions in Central and Eastern Europe M. Mierzwiak & K. Kroszczyński https://doi.org/10.3390/en16134969
3264. Accelerated design for elastocaloric performance in NiTi-based alloys through machine learning X. Tian et al. https://doi.org/10.1063/5.0068290
3265. Análise da Evolução Temporal de Garimpo Ilegal Sobre a Terra Indígena Kayapó M. Aviz et al. https://doi.org/10.26848/rbgf.v18.3.p2069-2086
3266. An integral and multidimensional review on multi-layer perceptron as an emerging tool in the field of water treatment and desalination processes A. Reza et al. https://doi.org/10.1016/j.desal.2024.117849
3267. TG-PGAT: An AIS Data-Driven Dynamic Spatiotemporal Prediction Model for Ship Traffic Flow in the Port J. Ma et al. https://doi.org/10.3390/jmse12101875
3268. Spectral feature selection algorithm based on improved zebra optimization algorithm for milk powder fat content detection W. Zhang et al. https://doi.org/10.1016/j.jfca.2025.108234
3269. Enhancing Safety Risk Management with Quantitative Measures B. Claros et al. https://doi.org/10.3141/2603-01
3270. Integrating molecular simulations with multilayer perceptron neural networks to predict the CH4/H2 adsorption and separation of MTV-MOFs Y. Xie et al. https://doi.org/10.1016/j.ijhydene.2025.04.407
3271. Analog Design and Machine Learning: A Review K. Liakos & F. Plessas https://doi.org/10.3390/electronics14173541
3272. On the measurement of enhanced energy storage in composite concentric helical pipes with RSA-DNN verification L. Chang et al. https://doi.org/10.1016/j.measurement.2025.119154
3273. Bridging Experimentation and Computation: OMSP for Advanced Acrylate Characterization and Digital Photoresin Design in Vat Photopolymerization L. Okoruwa et al. https://doi.org/10.3390/polym17020203
3274. An Improved VMD–EEMD–LSTM Time Series Hybrid Prediction Model for Sea Surface Height Derived from Satellite Altimetry Data H. Chen et al. https://doi.org/10.3390/jmse11122386
3275. Data-driven model assessment: A comparative study for ship response determination A. La Ferlita et al. https://doi.org/10.1016/j.oceaneng.2024.119711
3276. Image-Based Assessment of External Quality Traits in Chinese Bayberry (Myrica rubra) Using a Deep Learning Detection and Multi-Trait Scoring Framework M. Wang et al. https://doi.org/10.3390/foods15162852
3277. Prediction Uncertainty of Density Functional Approximations for Properties of Crystals with Cubic Symmetry P. Pernot et al. https://doi.org/10.1021/jp509980w
3278. PD-count: Prompt-driven zero-shot object counting with dynamic frequency transformation K. Liu et al. https://doi.org/10.1016/j.eswa.2026.131295
3279. Missing data treatment for locally weighted partial least square‐based modelling: A comparative study W. Yeo et al. https://doi.org/10.1002/apj.2422
3280. Brain Age Prediction/Classification through Recurrent Deep Learning with Electroencephalogram Recordings of Seizure Subjects K. Jusseaume & I. Valova https://doi.org/10.3390/s22218112
3281. Modeling cover management factor of RUSLE using very high-resolution satellite imagery in a semiarid watershed C. Vatandaşlar & M. Yavuz https://doi.org/10.1007/s12665-017-6388-0
3282. How good are different machine and deep learning models in forecasting the future price of metals? Full sample versus sub-sample A. Varshini et al. https://doi.org/10.1016/j.resourpol.2024.105040
3283. Comparative evaluation of the predictability of neural network methods on the flammability characteristics of extruded polystyrene from microscale combustion calorimetry R. Mensah et al. https://doi.org/10.1007/s10973-019-08335-0
3284. Data-driven prediction of building energy consumption using an adaptive multi-model fusion approach P. Lin et al. https://doi.org/10.1016/j.asoc.2022.109616
3285. A Contactless Measuring Speed System of Belt Conveyor Based on Optical Flow Techniques Y. Gao et al. https://doi.org/10.1109/ACCESS.2019.2937317
3286. Prediction of Cooling Load of Tropical Buildings with Machine Learning G. Bekdaş et al. https://doi.org/10.3390/su15119061
3287. Integrating Thermal Infrared Imaging and Weather Data for Short-Term Prediction of Building Envelope Thermal Appearance N. Golosov & G. Cervone https://doi.org/10.3390/rs16213981
3288. Dual-Domain Temporal–Spatial Denoising Approach for Autism Spectrum Disorder EEG Signals Based on Stationary Wavelet Transform and SPHARA C. Syiva et al. https://doi.org/10.62411/jcta.15875
3289. Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms S. Ghimire et al. https://doi.org/10.1016/j.apenergy.2019.113541
3290. Quantification of river total phosphorus using integrative artificial intelligence models S. Kim et al. https://doi.org/10.1016/j.ecolind.2023.110437
3291. Skill of CMIP5 models in simulating rainfall over Malawi B. Libanda & N. Nkolola https://doi.org/10.1007/s40808-019-00611-0
3292. Estimating lake okeechobee’s water volume using NDWI-derived remote sensing and genetic algorithm optimization on Google Earth Engine G. Golmohammadi et al. https://doi.org/10.1007/s43832-025-00255-5
3293. Predicting the Effect of Plasma Treatment on the Fading of Sulphur-Dyed Cotton Fabric Using Bayesian Regulated Neural Network (BRNN) and Gaussian Process Regression (GPR) S. Liu et al. https://doi.org/10.1007/s12221-023-00426-y
3294. Application of Digital Twins to Overhead Line Conductors M. Markovits et al. https://doi.org/10.3390/metrology6040071
3295. Augmenting post-hoc explanations for predictive process monitoring with uncertainty quantification via conformalized Monte Carlo dropout N. Mehdiyev et al. https://doi.org/10.1016/j.datak.2024.102402
3296. Analysis of Future Solar Power Potential Using CORDEX-CORE Ensemble in Côte d’Ivoire, West Africa N. Kouadio et al. https://doi.org/10.3390/en19071589
3297. Leveraging remote sensing–enabled machine learning for river water quality prediction in South Florida's hydrological systems M. Berihun et al. https://doi.org/10.1016/j.rsase.2025.101616
3298. Dynamic Production Order Allocation for Distributed Additive Manufacturing I. Sousa Agostino et al. https://doi.org/10.1016/j.ifacol.2020.12.2832
3299. Machine learning to predict refractory corrosion during nuclear waste vitrification N. Smith-Gray et al. https://doi.org/10.1557/s43580-021-00031-2
3300. A Decision-Making Methodology Based on Expert Systems Applied to Machining Tools Condition Monitoring M. Casal-Guisande et al. https://doi.org/10.3390/math10030520
3301. Integrating Statistical and Machine-Learning Approaches for Salmonella enterica Surveillance in Northwestern Italy: A One Health Data-Driven Framework A. Garcia-Vozmediano et al. https://doi.org/10.3390/microorganisms13122773
3302. Towards robust smart data-driven soil erodibility index prediction under different scenarios A. Shirzadi et al. https://doi.org/10.1080/10106049.2022.2076918
3303. A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters L. Wang et al. https://doi.org/10.1109/OJPEL.2026.3710206
3304. Optical and mechanical properties of Zr-oxide doped TiO2/SiO2 anti-reflective coatings for PV glass covers D. Zambrano-Mera et al. https://doi.org/10.1016/j.solmat.2022.111784
3305. Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors H. Sanikhani et al. https://doi.org/10.1016/j.compag.2018.07.008
3306. Broad learning approach to Surrogate-Assisted Multi-Objective evolutionary fuzzy clustering algorithm based on reference points for color image segmentation F. Zhao et al. https://doi.org/10.1016/j.eswa.2022.117015
3307. In silico design of novel FAK inhibitors using integrated molecular docking, 3D-QSAR and molecular dynamics simulation studies P. Shirvani & A. Fassihi https://doi.org/10.1080/07391102.2021.1875880
3308. Data-Driven Hybrid Model for Forecasting Wastewater Influent Loads Based on Multimodal and Ensemble Deep Learning S. Heo et al. https://doi.org/10.1109/TII.2020.3039272
3309. Deep learning model comparison and input variable optimization for enhanced pressure forecasting in water distribution networks M. Kim et al. https://doi.org/10.11001/jksww.2026.40.2.241
3310. Seismically Induced Liquefaction Potential Assessment by Different Artificial Intelligence Procedures D. Kumar et al. https://doi.org/10.1007/s40515-023-00327-w
3311. Rapid prediction of mine tunnel fire smoke movement with machine learning and supercomputing techniques Y. Hong et al. https://doi.org/10.1016/j.firesaf.2021.103492
3312. A novel hybrid image fusion method based on integer lifting wavelet and discrete cosine transformer for visual sensor networks B. Latreche et al. https://doi.org/10.1007/s11042-018-6676-z
3313. Application of exponential smoothing method and SARIMA model in predicting the number of admissions in a third-class hospital in Zhejiang Province W. Yang et al. https://doi.org/10.1186/s12889-023-17218-x
3314. Integrating remote sensing, GIS, and machine learning for lineament analysis and hydrogeological assessment in the Northern Atlasic domain of Tunisia I. Ben Slimene et al. https://doi.org/10.1016/j.jafrearsci.2026.106210
3315. Abundance distributions for tree species in Great Britain: A two‐stage approach to modeling abundance using species distribution modeling and random forest L. Hill et al. https://doi.org/10.1002/ece3.2661
3316. Tensile strength of different types of limestone rocks in north of Iraq D. Mohammed et al. https://doi.org/10.1007/s41062-021-00620-y
3317. Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete D. Dao et al. https://doi.org/10.3390/ma12060983
3318. Handling Missing Values Based on Similarity Classifiers and Fuzzy Entropy Measures F. Karim et al. https://doi.org/10.3390/electronics11233929
3319. Soil Moisture Satellite Data Under Scrutiny: Assessing Accuracy Through Environmental Proxies and Extended Triple Collocation Analysis A. Pataki et al. https://doi.org/10.1007/s41748-025-00605-2
3320. Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys S. Hossein Zadeh et al. https://doi.org/10.1016/j.matdes.2024.113096
3321. Predicting the distribution of Coilia nasus abundance in the Yangtze River estuary: From interpolation to extrapolation Y. Wang et al. https://doi.org/10.1016/j.ecss.2024.108935
3322. Enhancing monthly extreme water level predictions in a flood-prone river basin using regression-based machine learning M. Islam et al. https://doi.org/10.2166/h2oj.2025.016
3323. Theoretical Recommendations and Validation for the Generation of Realistic Irregular Waves Through the WaveMIMO Methodology M. Paiva et al. https://doi.org/10.3390/pr13051395
3324. Reliability of empirical equations to predict uniaxial compressive strength of rocks using Schmidt hammer D. Mohammed et al. https://doi.org/10.1080/17499518.2019.1658881
3325. CO2 Emisyonu ve Birincil Enerji Tüketimi Arasındaki İlişkinin Kantil Regresyon Modeli ile İncelenmesi H. AKYÜZ https://doi.org/10.29130/dubited.1076185
3326. A data-driven geometry-specific surrogate model for forecasting the load–displacement behavior until ductile fracture S. Dey & R. Kiran https://doi.org/10.1007/s10704-025-00839-1
3327. A dropout weight-constrained recurrent neural network model for forecasting the price of major cryptocurrencies and CCi30 index I. Livieris et al. https://doi.org/10.1007/s12530-020-09361-2
3328. WITHDRAWN: Impact of Lag Window Configuration on Next-Day River Water Stage Forecasting Accuracy: Comparative Evaluation of Six Machine Learning and Deep Learning Algorithms M. Islam et al. https://doi.org/10.1016/j.htopen.2026.100006
3329. Comparison of growth curve models for Ongole Grade cattle Y. Adinata et al. https://doi.org/10.1007/s11250-022-03254-z
3330. The right-of-way assignment strategy under mixed traffic: considering drivers’ confidence in CAVs F. Zong et al. https://doi.org/10.1080/21680566.2024.2441460
3331. Combining Content-Based Filtering Methods for Building a Powerful Hybrid Recommender System to Improve Tourism in Drâa-Tafilalet Area K. Fararni et al. https://doi.org/10.3390/technologies14070421
3332. Time Series Prediction Based on Multi-Scale Feature Extraction R. Zhang & Y. Hao https://doi.org/10.3390/math12070973
3333. Investigating catchment predictors of the fraction of young water variability in streamflow in mesoscale Precambrian Shield catchments in Northeastern Ontario, Canada F. Eebo et al. https://doi.org/10.1016/j.jhydrol.2026.136039
3334. Impact of Time Step Size on Different Cumulus Parameterization Schemes in the Numerical Simulation of a Heavy Rainfall Event Over Tamil Nadu, India K. Singh et al. https://doi.org/10.1007/s00024-021-02896-8
3335. A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise F. Weigend et al. https://doi.org/10.1007/s10479-022-04947-2
3336. Effect of heat and moisture transfer on the growth of mould on the inner surface of walls: A case study in Dalian of China Y. Lv et al. https://doi.org/10.1007/s12273-020-0666-6
3337. A robust factor analysis model based on the canonical fundamental skew-t distribution T. Lin et al. https://doi.org/10.1007/s00362-022-01318-8
3338. Simulating field-scale variability and precision management with a 3D hydrologic cropping systems model N. Ward et al. https://doi.org/10.1007/s11119-017-9517-6
3339. Automated Labeling of Movement- Related Cortical Potentials Using Segmented Regression U. Rashid et al. https://doi.org/10.1109/TNSRE.2019.2913880
3340. Efecto del refinamiento de la descripción de la rugosidad en una aproximación 2D para un río de montaña: un caso de estudio J. Cedillo Galarza et al. https://doi.org/10.17163/lgr.n33.2021.08
3341. A Maieutic Exploration of Nudging Strategies for Regional Climate Applications Using the WRF Model T. Spero et al. https://doi.org/10.1175/JAMC-D-17-0360.1
3342. Closed-Form Models of Accuracy Loss due to Subsampling in SVD Collaborative Filtering S. Poudel & M. Bikdash https://doi.org/10.26599/BDMA.2022.9020024
3343. A digitized approach for amplitude-integrated electroencephalogram transformation towards a standardized procedure C. Chen et al. https://doi.org/10.1016/j.bspc.2021.102433
3344. Artificial intelligence prediction algorithms for refractive error onset and progression in children and adolescents: A systematic review and meta‐analysis A. Sandali et al. https://doi.org/10.1111/aos.70207
3345. Storm Surge Modeling in Large Estuaries: Sensitivity Analyses to Parameters and Physical Processes in the Chesapeake Bay J. Garzon & C. Ferreira https://doi.org/10.3390/jmse4030045
3346. HCLmNet: A unified hybrid continual learning strategy multimodal network for lung cancer survival prediction M. Bappi et al. https://doi.org/10.1371/journal.pone.0316509
3347. Estimating Annual Wildfire-Related Potential Above-Ground Biomass Loss in Eastern Canadian Boreal Forests Using Multi-Source Remote Sensing and XGBoost H. Mahmoudi Meimand et al. https://doi.org/10.3390/rs18173022
3348. Interpretation and diagnosis of fouling progress in membrane bioreactor plants using a periodic pattern recognition method K. Nam et al. https://doi.org/10.1007/s11814-017-0197-8
3349. Reply on “Reply to comment on Important notes on parameter estimation of solar photovoltaic cell”, by Gnetchejo et al. [Energy Conversion and Management, https://doi.org/10.1016/ j.enconman.2019.111870] D. Yousri et al. https://doi.org/10.1016/j.enconman.2019.112234
3350. Trading Off Scalability, Privacy, and Performance in Data Synthesis X. Ling et al. https://doi.org/10.1109/ACCESS.2024.3366556
3351. Developing machine learning models for predicting daily relative humidity and solar radiation using lagged time series data inputs in a semi-arid climate J. Rajput et al. https://doi.org/10.1016/j.jastp.2025.106619
3352. Application of multivariate recursive nesting bias correction, multiscale wavelet entropy and AI-based models to improve future precipitation projection in upstream of the Heihe River, Northwest China L. Yang et al. https://doi.org/10.1007/s00704-018-2598-y
3353. Evaluation of Table Grape Flavor Based on Deep Neural Networks Z. Liu et al. https://doi.org/10.3390/app13116532
3354. Unmixing marsh vegetation species across multiple sensors and spatial scales Z. Yang et al. https://doi.org/10.1080/15481603.2025.2481689
3355. Selecting appropriate machine learning methods for digital soil mapping Y. Khaledian & B. Miller https://doi.org/10.1016/j.apm.2019.12.016
3356. A Hybrid System for Automated Assessment of Korean L2 Writing: Integrating Linguistic Features with LLM W. Hur & B. Ji https://doi.org/10.3390/systems13100851
3357. Deep Learning Improves Planting Year Estimation of Macadamia Orchards in Australia A. Clark et al. https://doi.org/10.3390/agriculture15222346
3358. An Improved PV Output Forecasting Model by Using Weight Function: A Case Study in Cambodia S. Kittisontirak et al. https://doi.org/10.1155/2016/2616750
3359. Validation of age estimation methods through the scapula in a Mediterranean non-adult population M. Nogueras López et al. https://doi.org/10.1007/s00414-024-03192-5
3360. Exploring biophysical links of catch rate from mid-water trawl fishery in the north-west coast of India, Eastern Arabian Sea: A remote sensing approach P. Azeez et al. https://doi.org/10.1016/j.scitotenv.2023.163975
3361. Discovering mathematical formulas from data via GPT-guided Monte Carlo Tree Search Y. Li et al. https://doi.org/10.1016/j.eswa.2025.127591
3362. New approach to evaluating predictive models of photovoltaic systems P. Dobreva et al. https://doi.org/10.1016/j.solener.2020.04.028
3363. Comparison of collision dynamics of soccer balls with energy dissipation method A. Tunçel et al. https://doi.org/10.1177/17543371241237589
3364. Evaluation of General Circulation Models over the Upper Ouémé River Basin in the Republic of Benin A. Attogouinon et al. https://doi.org/10.3390/hydrology7010011
3365. Coupled model on the variation of diffusion coefficient and surface chloride concentration in reinforced concrete structures over time T. Reichert et al. https://doi.org/10.1016/j.conbuildmat.2023.134715
3366. Comparing high-resolution snow mapping approaches in palsa mires: UAS lidar vs. modelling A. Störmer et al. https://doi.org/10.5194/tc-19-3949-2025
3367. Hybrid Machine Learning-Geostatistical Framework for Sustainable Spatiotemporal Temperature Forecasting N. Iqbal et al. https://doi.org/10.3390/su18147193
3368. Numerical Study and Geometrical Investigation of an Onshore Overtopping Device Wave Energy Converter with a Seabed Coupled Structure A. de Barros et al. https://doi.org/10.3390/jmse11020412
3369. An interpretable boosting-based predictive model for transformation temperatures of shape memory alloys S. Zadeh et al. https://doi.org/10.1016/j.commatsci.2023.112225
3370. Empirical Validation of a Multidirectional Ultrasonic Pedestrian Detection System for Heavy-Duty Vehicles Under Adverse Weather Conditions H. Jeong & J. Kim https://doi.org/10.3390/s25175287
3371. A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling J. Tuttle et al. https://doi.org/10.1016/j.apenergy.2021.116886
3372. A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste M. Zaki et al. https://doi.org/10.1021/acsestengg.3c00043
3373. Multi-Method Explainable AI Framework for Quantifying Traffic and Meteorological Contributions to Urban Air Pollution: A Case Study of Istanbul’s Bosphorus Bridge Corridor E. Birinci et al. https://doi.org/10.3390/atmos17060591
3374. Novel Hybrid Data-Intelligence Model for Forecasting Monthly Rainfall with Uncertainty Analysis Z. Yaseen et al. https://doi.org/10.3390/w11030502
3375. What is the Accuracy of PEEK Implants for Cranioplasty in Comparison to Their Patient Specific Surgical Plan? A. Wandell et al. https://doi.org/10.1016/j.joms.2022.09.004
3376. River flow prediction using hybrid PSOGSA algorithm based on feed-forward neural network S. Meshram et al. https://doi.org/10.1007/s00500-018-3598-7
3377. Uncertainty propagation in a modelling chain of climate change impact for a representative French drainage site A. Jeantet et al. https://doi.org/10.1080/02626667.2023.2203322
3378. Predicting fetal health using ANFIS: A comparative study with machine learning models J. Sade https://doi.org/10.31127/tuje.1711661
3379. The influence of sample size on two approaches to estimate Black Grouse Lyrurus tetrix population size using non‐invasive sampling methods M. Haider et al. https://doi.org/10.1111/ibi.13229
3380. Coupling GIS with Stormwater Modelling for the Location Prioritization and Hydrological Simulation of Permeable Pavements in Urban Catchments D. Jato-Espino et al. https://doi.org/10.3390/w8100451
3381. Investigation of the effects of various parameters on wireless power transfer efficiency M. Yilmaz et al. https://doi.org/10.1016/j.aeue.2025.155723
3382. CaPITeN: Design and validation of an innovative methodology for thermal and visual comfort assessment in tropical climates T. Rakotoarivelo & B. Malet-Damour https://doi.org/10.1016/j.buildenv.2026.114777
3383. Electronic structure–performance relationship in pyridine-based Schiff bases: a dual experimental–DFT study on corrosion inhibition Q. Yousif & M. Bedair https://doi.org/10.1039/D6RA05353J
3384. Predicting the Path of Insurgency: Data-Driven Strategies to Counter Boko Haram in Nigeria J. Braimah et al. https://doi.org/10.12688/f1000research.153978.1
3385. Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea I. Seo et al. https://doi.org/10.1371/journal.pone.0321530
3386. Effects of complex terrain on net surface longwave radiation in China X. Zhu et al. https://doi.org/10.1007/s00704-017-2272-9
3387. The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation D. Chicco et al. https://doi.org/10.7717/peerj-cs.623
3388. SHAP-based explainable machine learning for district-wise real-time water quality monitoring in bihar using IoT sensors Z. Afshan et al. https://doi.org/10.1088/2631-8695/ae5ec0
3389. A non destructive testing method for masonry by using UPV and cross validation procedure E. Vasanelli et al. https://doi.org/10.1617/s11527-020-01568-8
3390. MODIS Evapotranspiration Forecasting Using ARIMA and ANN Approach at a Water-Stressed Irrigation Scheme in South Africa M. Phesa et al. https://doi.org/10.3390/hydrology11100176
3391. Evaluating the Traffic Noise Levels at Median U-Turns under Heterogeneous Traffic Conditions in Makassar City M. Hustim et al. https://doi.org/10.48084/etasr.11378
3392. Simulation-Driven Deep Transfer Learning Framework for Data-Efficient Prediction of Physical Experiments S. Lim et al. https://doi.org/10.3390/math13233884
3393. Modelling Cloud Cover Climatology over Tropical Climates in Ghana F. Dogbey et al. https://doi.org/10.3390/atmos13081265
3394. dSPACE Controller-Based Enhanced Piezoelectric Energy Harvesting System Using PI-Lightning Search Algorithm M. Sarker et al. https://doi.org/10.1109/ACCESS.2018.2888912
3395. A hybrid data-driven methodology for forecasting normal and extreme electricity prices S. Loizidis et al. https://doi.org/10.1016/j.egyai.2026.100916
3396. Machine-learning-based prediction of early-age compressive strength of ultra-high-performance concrete using ultrasonic pulse velocity and rebound hammer H. Wu et al. https://doi.org/10.1016/j.conbuildmat.2026.147023
3397. Performance assessment of CORDEX regional climate models in wind speed simulations over Zambia B. Libanda https://doi.org/10.1007/s40808-022-01504-5
3398. How accurate is accurate enough? Assessing the influence of exposure data quality on tsunami damage modelling using the 2011 Tōhoku tsunami C. Geiß et al. https://doi.org/10.1016/j.pdisas.2026.100765
3399. Hybrid prediction strategy to predict agricultural information K. Aditya Shastry & H. Sanjay https://doi.org/10.1016/j.asoc.2020.106811
3400. Development of a Short-Form Stroke Impact Scale Using a Machine Learning Algorithm for Patients at the Subacute Stage S. Lee et al. https://doi.org/10.5014/ajot.2022.049136
3401. UAV multi-source data fusion with super-resolution for accurate soybean leaf area index estimation Z. Zhao et al. https://doi.org/10.3389/fpls.2025.1700660
3402. POINT-BY-POINT AND COMPLEX QUALITY METRICS IN ATMOSPHERE AND OCEAN RESEARCH: REVIEW OF METHODS AND APPROACHES V. Rezvov et al. https://doi.org/10.29006/1564-2291.JOR-2024.52(4).10
3403. Harnessing the power of transformers and data fusion in smart irrigation B. Deforce et al. https://doi.org/10.1016/j.asoc.2024.111246
3404. Habitat quality on the edge of anthropogenic pressures: Predicting the impact of land use changes in the Brazilian Upper Paraguay river Basin M. Broquet et al. https://doi.org/10.1016/j.jclepro.2024.142546
3405. Assessing the impact of climate change on groundwater level changes using ensemble models S. Afrifa et al. https://doi.org/10.1007/s40899-025-01245-0
3406. A surrogate-based inverse design framework for targeted diameter control of electrospun nanofibers M. Mahdian et al. https://doi.org/10.1038/s41598-026-40692-3
3407. Comparative study of PV power forecast using parametric and nonparametric PV models M. Almeida et al. https://doi.org/10.1016/j.solener.2017.07.032
3408. Numerical Study and Parametric Insights of Mechanized Shaft Excavation in Soft Clay S. Rivera et al. https://doi.org/10.3390/buildings16102045
3409. AIM5LA: A Latency-Aware Deep Reinforcement Learning-Based Autonomous Intersection Management System for 5G Communication Networks G. Antonio & C. Maria-Dolores https://doi.org/10.3390/s22062217
3410. MHA-SVR: An Adaptive Soft Sensor Based on Feature Interaction for Ultrasonic Phytomedicine Extraction Y. Yue et al. https://doi.org/10.2174/0115680266356325250510064641
3411. Prediction of flood routing results in the Central Anatolian region of Türkiye with various machine learning models O. Katipoğlu & M. Sarıgöl https://doi.org/10.1007/s00477-023-02389-1
3412. Trivariate Probabilistic Assessments of the Compound Flooding Events Using the 3-D Fully Nested Archimedean (FNA) Copula in the Semiparametric Distribution Setting S. Latif & S. Simonovic https://doi.org/10.1007/s11269-023-03448-6
3413. Quantitative determination for multiple indicators of lard using machine learning and Raman spectroscopy: A PCA-KNN-based framework with automated optimization of hyperparameters Z. Ma et al. https://doi.org/10.1016/j.foodcont.2025.111813
3414. ALRC: A Novel Adaptive Linear Regression Based Classification for Grade based Student Learning using Radio Frequency Identification P. Arulmozhi et al. https://doi.org/10.1007/s11277-020-07141-4
3415. Effectiveness of statistical and soft computing techniques in predicting slake durability index of sedimentary rocks in Chotanagpur Plateau in India – A case study A. Kumar et al. https://doi.org/10.1007/s10064-026-04868-5
3416. Analysis & forecasting of juvenile crime using variance threshold and time series algorithm H. Jain & R. Patel https://doi.org/10.1007/s11042-024-19780-x
3417. Understanding green house gases emission dynamics from forest fires in Thailand using predictive models F. Shahzad et al. https://doi.org/10.1016/j.gloplacha.2025.105236
3418. Multi-Objective Optimization of Petroleum Engineering Problems Using a Hybrid Workflow: Combination of Combination of Particle Swarm Optimization, Fuzzy Logic, Imperialist Competitive Algorithm and Response Surface Methodology M. Karambeigi et al. https://doi.org/10.2139/ssrn.4170655
3419. Application of meta-heuristic hybrid models in estimating the average air temperature of Caspian sea coast of Iran H. Babaali et al. https://doi.org/10.1016/j.envc.2024.101039
3420. A fog-assisted group-based truth discovery framework over mobile crowdsensing data streams B. Alamri et al. https://doi.org/10.1371/journal.pone.0330656
3421. Assessment and validation of two prediction models of MUF in China Q. Yu et al. https://doi.org/10.1016/j.asr.2026.05.027
3422. Irregularly sampled seismic data interpolation via wavelet-based convolutional block attention deep learning Y. Lou et al. https://doi.org/10.1016/j.aiig.2022.12.001
3423. Application of Fuzzy Control and Neural Network Control in the Commercial Development of Sustainable Energy System F. Xie et al. https://doi.org/10.3390/su16093823
3424. Multi-horizon hourly air temperature forecasting over Lake Van using classical, machine learning, and transformer-based models: a comparative benchmark with statistical significance testing M. Güneş https://doi.org/10.1007/s10651-026-00746-1
3425. Quantifying physical degradation alongside recording and stimulation performance of 980 intracortical microelectrodes chronically implanted in three humans for 956-2130 days D. Bjånes et al. https://doi.org/10.1016/j.actbio.2025.02.030
3426. Drainage Duration Variability and PALSAR-2 Sensitivity to Rice-Field Water Status: Insights from Large-Scale In Situ Water-Level Observations X. Jin et al. https://doi.org/10.3390/rs18132136
3427. Generative machine learning for skilful 3D radar nowcasting J. Wan et al. https://doi.org/10.1038/s41612-026-01407-7
3428. A hybrid time series forecasting model combining recurrent neural networks and ensemble learning for furniture sales prediction O. Şahin & B. Çubukçu https://doi.org/10.1016/j.asej.2026.104219
3429. A comparative analysis of biomass torrefaction severity index prediction from machine learning W. Chen et al. https://doi.org/10.1016/j.apenergy.2022.119689
3430. An exploratory analysis of regression methods for predicting faults in software systems S. Rathore https://doi.org/10.1007/s00500-021-06048-x
3431. Impact of Environmental Conditions on Renewable Energy Prediction: An Investigation Through Tree-Based Community Learning F. Doğan et al. https://doi.org/10.3390/app15010336
3432. Multiscale Spatial–Spectral Invertible Compensation Network for Hyperspectral Remote Sensing Image Denoising H. Li et al. https://doi.org/10.1109/TGRS.2024.3457010
3433. A two-layer elasto-visco-plastic rheological model for the material parameter identification of bone tissue A. Reisinger et al. https://doi.org/10.1007/s10237-020-01329-0
3434. Assessment of Leachate Production from a Municipal Solid-Waste Landfill through Water-Balance Modeling S. Beck-Broichsitter et al. https://doi.org/10.3390/geosciences8100372
3435. Research on quality control methods for surface temperature observations via spatial correlation analysis X. Xiong et al. https://doi.org/10.1002/joc.7897
3436. Comparison of random forest and support vector machine regression models for forecasting road accidents A. Gatera et al. https://doi.org/10.1016/j.sciaf.2023.e01739
3437. Machine learning investigation of chemical disorder effects in 24-valence-electron full-Heusler alloys with single magnetic element Y. Guo et al. https://doi.org/10.1016/j.jmmm.2025.173322
3438. The Data-Driven Modeling of Pressure Loss in Multi-Batch Refined Oil Pipelines with Drag Reducer Using Long Short-Term Memory (LSTM) Network S. Wang et al. https://doi.org/10.3390/en14185871
3439. Machine-learning models for predicting CO2 solubility in various brine systems: implications for carbon geo-storage S. Davoodi et al. https://doi.org/10.1016/j.molliq.2025.128122
3440. The impact of SDG information on equality, sustainability behaviors, and sustainable entrepreneurial intention: A hybrid SEM–ANN approach L. Cabeza-Ramírez et al. https://doi.org/10.1016/j.ijme.2026.101474
3441. Solar irradiance prediction with variable time lengths and multi-parameters in full climate conditions based on photovoltaic greenhouse Y. Zhu et al. https://doi.org/10.1016/j.enconman.2024.118758
3442. EU Net-Zero Policy Achievement Assessment in Selected Members through Automated Forecasting Algorithms C. Tudor & R. Sova https://doi.org/10.3390/ijgi11040232
3443. An Investigation into the Applicability of the SHUD Model for Streamflow Simulation Based on CMFD Meteorological Data in the Yellow River Source Region T. Bu et al. https://doi.org/10.3390/w16243583
3444. Regression applied to legal judgments to predict compensation for immaterial damage T. Dal Pont et al. https://doi.org/10.7717/peerj-cs.1225
3445. A novel blocked based U-Net model for image steganography A. Sk et al. https://doi.org/10.1007/s11042-025-20952-6
3446. Drive System Inverter Modeling Using Symbolic Regression M. Glučina et al. https://doi.org/10.3390/electronics12030638
3447. Unified 3E modeling and capacity planning for micro-energy systems J. Chen et al. https://doi.org/10.1016/j.energy.2026.140349
3448. The Feasibility Surface: Mapping the Landscape of Run-of-River Hydropower Potential G. Alcalá et al. https://doi.org/10.3390/en19153568
3449. How to best map greenery from a human perspective? Comparing computational measurements with human perception J. Torkko et al. https://doi.org/10.3389/frsc.2023.1160995
3450. A computational framework for analyzing urban data usage patterns in African cities: a 25-year data-driven review using natural language processing and machine learning R. Azmi et al. https://doi.org/10.1016/j.cacint.2026.100296
3451. Effects of Tire Dynamics on Vehicle Safety: A Simulation-Driven Comparison of New and Service-Aged Tires Under Variable Inflation Pressures and Loads M. Karpenko et al. https://doi.org/10.3390/machines14091002
3452. Kriging-based approach to predict missing air temperature data A. Shtiliyanova et al. https://doi.org/10.1016/j.compag.2017.09.033
3453. Impact of Sustainable Development and Environmental Protection on the Volume of Domestic Hard Coal Sales in Poland A. Rybak & E. Włodarczyk https://doi.org/10.3390/en15020443
3454. Development of a modified Green–Ampt model considering the unsaturated zone Y. Li et al. https://doi.org/10.1016/j.biosystemseng.2025.104174
3455. Automated and manual model creation workflows are equally reliable for virtual mechanical testing of ovine bone and fracture healing M. Bahrami et al. https://doi.org/10.1038/s41598-025-32307-0
3456. A survey of recommender systems for energy efficiency in buildings: Principles, challenges and prospects Y. Himeur et al. https://doi.org/10.1016/j.inffus.2021.02.002
3457. Research on a Real-Time Estimation Method of Vehicle Sideslip Angle Based on EKF W. Sun et al. https://doi.org/10.3390/s22093386
3458. A Comparative Study of Single and Multi-Stage Forecasting Algorithms for the Prediction of Electricity Consumption Using a UK-National Health Service (NHS) Hospital Dataset A. Taha et al. https://doi.org/10.3390/fi15040134
3459. Integrated Machine Learning and Health Risk Assessment for Groundwater Nitrate Contamination in Handan City, China Y. Zhao et al. https://doi.org/10.3390/w18101174
3460. Deciphering the mechanisms of arsenic adsorption on MOF membranes via a machine learning framework incorporating attention mechanisms Y. Wu et al. https://doi.org/10.1016/j.jece.2026.124452
3461. Achieving Privacy-Preserving and Lightweight Truth Discovery in Mobile Crowdsensing J. Tang et al. https://doi.org/10.1109/TKDE.2021.3054409
3462. An electricity load forecasting model based on multilayer dilated LSTM network and attention mechanism Y. Wang et al. https://doi.org/10.3389/fenrg.2023.1116465
3463. Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis S. Kashinath et al. https://doi.org/10.1109/ACCESS.2021.3069770
3464. Estimating evaporation in diverse iranian climates using hybrid metaheuristic algorithms and ANN H. Babaali et al. https://doi.org/10.1007/s13762-025-06975-4
3465. Analyzing the dynamic behavior and market efficiency of green energy investments: A geometric and fractional brownian motion approach M. Bozkurt et al. https://doi.org/10.1080/15567249.2025.2457438
3466. iSIM-Sigma: Efficient Standard Deviation Calculation for Molecular Similarity K. Lopez-Perez et al. https://doi.org/10.1021/acs.jcim.5c00894
3467. Urban meteorological forcing data for building energy simulations Y. Tang et al. https://doi.org/10.1016/j.buildenv.2021.108088
3468. Machine Learning Methods for Predicting the Performance of Cold‐Formed Steel Sections: A State‐of‐the‐Art Review G. Iyappan & P. Sangeetha https://doi.org/10.1002/tal.70079
3469. Multi-Objective Constrained Constellation Design and Characterization for Cislunar Space Object Tracking C. Chan & S. Singh https://doi.org/10.2514/1.A36646
3470. Ammonia emissions from livestock facilities around an international airport, Tehran, Iran: An experimental and mathematical study G. Asadollahfardi et al. https://doi.org/10.1002/ep.14359
3471. Explainable artificial intelligence for machine learning prediction of bandgap energies T. Masuda & K. Tanabe https://doi.org/10.1063/5.0226151
3472. Modeling hybrid nanofluid density using machine learning algorithms S. Uslu & A. Kocer https://doi.org/10.1007/s10973-026-15981-8
3473. Machine learning downscaling of satellite derived land surface temperature in the historic urban heritage area of São João del-Rei Brazil J. Neto et al. https://doi.org/10.1007/s44327-026-00318-9
3474. Adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) modelling of Cu, Cd, and Pb adsorption onto tropical soils B. Agbaogun et al. https://doi.org/10.1007/s11356-022-24296-8
3475. Progressive visual analysis of traffic data based on hierarchical topic refinement and detail analysis Y. Tao & Y. Tang https://doi.org/10.1007/s12650-022-00879-y
3476. How Wave‐Induced Forced Disturbance Affects the Stability of Variable‐Speed Seawater Pumped Storage Units: Stability Mechanism and Control Optimisation M. Li et al. https://doi.org/10.1049/rpg2.70386
3477. Backcasting and forecasting stabilized soil mechanical properties for mechanistic-empirical pavement design A. Carey & I. Howard https://doi.org/10.1016/j.conbuildmat.2022.126645
3478. Novel hybrid deep-long short-term memory and machine learning algorithms for the crack-healing estimation of eco-friendly engineered cementitious composites C. Kina & H. Tanyildizi https://doi.org/10.1016/j.asoc.2026.115277
3479. A probabilistic integration of LSTM and Gaussian process regression for uncertainty-aware reservoir water level predictions K. Tandon & S. Sen https://doi.org/10.1080/02626667.2024.2428428
3480. Influence of aviation low-pressure environment on the aging behavior and thermal safety of lithium titanate batteries X. Tao et al. https://doi.org/10.1016/j.est.2025.115488
3481. Low-Light and Infrared Multimodal Remote Sensing in Nighttime Rescue Mission: A Review of Anomaly Detection Methods Y. Wan et al. https://doi.org/10.1109/TGRS.2025.3568456
3482. Integrating optimization and machine learning for estimating water resistivity and saturation in shaley sand reservoirs M. Hameedy et al. https://doi.org/10.1038/s41598-026-36133-w
3483. Using Fuzzy Inference Systems for the Creation of Forex Market Predictive Models A. Hernandez-Aguila et al. https://doi.org/10.1109/ACCESS.2021.3077910
3484. Predicting the particle-agglomeration effect on the equivalent mechanical properties of dispersion nuclear fuel by machine learning Y. Dong et al. https://doi.org/10.1016/j.jnucmat.2023.154697
3485. A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff A. Aieb et al. https://doi.org/10.3390/s22093241
3486. Cepair: an AI-powered and fog-based predictive CEP system for air quality monitoring M. Şimsek et al. https://doi.org/10.1007/s10586-024-04434-2
3487. Organic carbon dominates soil porosity across environmental gradients, with organic carbon–clay metrics providing secondary insight A. Thomas et al. https://doi.org/10.1016/j.catena.2026.110657
3488. Forecasting for Battery Storage: Choosing the Error Metric C. Singleton & P. Grindrod https://doi.org/10.3390/en14196274
3489. Optimized Dissolved Oxygen Prediction Using Genetic Algorithm and Bagging Ensemble Learning for Smart Fish Farm P. Khan & Y. Byun https://doi.org/10.1109/JSEN.2023.3278719
3490. Deep learning-driven ultra-stretchable kirigami metamaterials: towards surface texture modulation via buckling Y. Zhang et al. https://doi.org/10.1039/D5SM00933B
3491. Evaluation of diffusion and Henry's coefficients of CO2 absorption using Response Surface Methodology and Artificial Neural Network models D. Behvandi et al. https://doi.org/10.1016/j.cscee.2024.100723
3492. Effects of Non-Uniform Data Coverage on Deep Neural Network-Based Scramjet Performance Prediction Â. Paulino et al. https://doi.org/10.1590/jatm.v18.1439
3493. A Fully Unsupervised Machine Learning Framework for Algal Bloom Forecasting in Inland Waters Using MODIS Time Series and Climatic Products P. Ananias et al. https://doi.org/10.3390/rs14174283
3494. Ordinary kriging as a data augmentation technique for enhanced total dissolved solids prediction in tropical wetlands using Sentinel-2 and machine learning D. Mejia Ávila et al. https://doi.org/10.1080/01431161.2026.2612850
3495. Mathematical modeling for solute transport in aquifer M. Singh et al. https://doi.org/10.2166/hydro.2015.034
3496. Machine Learning Models Applied to Manage the Operation of a Simple SWRO Desalination Plant and Its Application in Marine Vessels G. Marichal Plasencia et al. https://doi.org/10.3390/w13182547
3497. Remote Sensing-Based Leaf Area Index Estimation of Spring Wheat Through Machine-Learning Approaches P. Prakash et al. https://doi.org/10.1007/s12524-025-02347-0
3498. Correcting climate model simulations in Heihe River using the multivariate bias correction package Q. Zhu & W. Zhao https://doi.org/10.1007/s10651-018-0410-x
3499. Ensemble of steerable local neighbourhood grey-level information for binarization F. Kasmin et al. https://doi.org/10.1016/j.patrec.2017.07.014
3500. Addressing Spatial Variability in Estimating Cover Management Factor of Soil Erosion Models using Geoinformatics: A Case Study of Netravati Catchment, Karnataka, India W. Makhdumi et al. https://doi.org/10.1177/11786221251360407
3501. Population changes and growth modeling of Salmonella enterica during alfalfa seed germination and early sprout development W. Kim et al. https://doi.org/10.1007/s10068-018-0412-3
3502. Estimating runtime of a job in Hadoop MapReduce N. Peyravi & A. Moeini https://doi.org/10.1186/s40537-020-00319-4
3503. Presenting new approaches based on Zhao–Atlas–Marks distribution and machine learning for detecting structural damage in steel beams H. Ahmadi et al. https://doi.org/10.1108/IJSI-04-2025-0088
3504. Analysis of pile load-settlement prediction using finite element method and deep neural network M. Kabir et al. https://doi.org/10.1088/2631-8695/ae1dcc
3505. Predicting Swarm Equatorial Plasma Bubbles via Machine Learning and Shapley Values S. Reddy et al. https://doi.org/10.1029/2022JA031183
3506. Constraining a density-dependent flow model with the transient electromagnetic method in a coastal aquifer in Mexico to assess seawater intrusion J. Torres-Martinez et al. https://doi.org/10.1007/s10040-019-02024-w
3507. Monte Carlo Dropout Neural Networks for Forecasting Sinusoidal Time Series: Performance Evaluation and Uncertainty Quantification U. Kummaraka & P. Srisuradetchai https://doi.org/10.3390/app15084363
3508. Forecast and analysis of fluctuating China containerized freight index: from the perspective of EEMD-LSTM modeling F. Wenwen et al. https://doi.org/10.1080/03088839.2025.2605989
3509. CR-former: Single-Image Cloud Removal With Focused Taylor Attention Y. Wu et al. https://doi.org/10.1109/TGRS.2024.3506780
3510. Sparse machine learning assisted deep computational insights on the mechanical properties of graphene with intrinsic defects and doping K. Gupta et al. https://doi.org/10.1016/j.jpcs.2021.110111
3511. Interpretable Machine Learning for Monthly Mean Air Temperature Modeling Under Correlated Meteorological Predictors: A Single-Station Case Study in Zonguldak, Türkiye R. Uzun Arslan et al. https://doi.org/10.3390/su18168458
3512. Fault detection and diagnosis for industrial processes based on clustering and autoencoders: a case of gas turbines J. Barrera et al. https://doi.org/10.1007/s13042-022-01583-x
3513. Temporal effects on glare response from daylight M. Kent et al. https://doi.org/10.1016/j.buildenv.2016.09.002
3514. ENSO-induced precipitation seasonality in the Chinese loess plateau during 1767–2050 CE L. Yi & L. Tan https://doi.org/10.1016/j.fmre.2025.04.010
3515. A Transformer-Based Deep Diffusion Model for Bulk RNA-Seq Deconvolution Y. Liu et al. https://doi.org/10.3390/biology14091150
3516. Evaluating the impact of multivariate imputation by MICE in feature selection M. Mera-Gaona et al. https://doi.org/10.1371/journal.pone.0254720
3517. Protein Stabilization in White Wine by Using a Flow-Through Fixed-Bed Adsorption Column: Analysis of Adsorption Isotherms and Breakthrough Curves E. Goktayoglu & R. Runnebaum https://doi.org/10.1021/acsfoodscitech.5c00985
3518. Evolution of Deep Neural Network Architecture Using Particle Swarm Optimization to Improve the Performance in Determining the Friction Angle of Soil T. Pham et al. https://doi.org/10.1155/2021/5570945
3519. Numerical models of hydrodynamics and marine debris in the Malacca Strait K. Ondara & S. Purnawan https://doi.org/10.1088/1755-1315/869/1/012053
3520. Analyzing the uncertainties between reanalysis meteorological data and ground measured meteorological data K. Ukhurebor et al. https://doi.org/10.1016/j.measurement.2020.108110
3521. Evaluating WRF simulated temperature uncertainties across Northern Hemisphere climate zones with different land surface models and land cover datasets B. Wang et al. https://doi.org/10.1016/j.atmosres.2026.108897
3522. Shortfall of B3LYP in Reproducing NMR JCH Couplings in Some Isomeric Epoxy Structures with Strong Stereoelectronic Effects: A Benchmark Study on DFT Functionals J. Adamson et al. https://doi.org/10.1002/cphc.201701125
3523. High-throughput spectral imaging combined with convolutional neural networks for simultaneous quantitative analysis of mixed anionic surfactants in aqueous environments H. Wang et al. https://doi.org/10.1039/D5AY01443C
3524. Correlation between subjective and objective assessment of magnetic resonance (MR) images L. Chow et al. https://doi.org/10.1016/j.mri.2016.03.006
3525. Machine learning strategies for predicting techno-functional properties of insect–plant ingredient blends A. Brena-Melendez et al. https://doi.org/10.1016/j.lwt.2026.119965
3526. A Novel Telescopic Cartesian Manipulator for Kiwifruit Harvesting with Hybrid Model–Vision Error Compensation B. Jia et al. https://doi.org/10.3390/agriculture16151673
3527. How urban surface and morphological features shape air and surface temperatures disparities: a spatiotemporal investigation in Hong Kong S. Li et al. https://doi.org/10.1016/j.cacint.2026.100453
3528. Long short-term memory for predicting daily suspended sediment concentration K. Kaveh et al. https://doi.org/10.1007/s00366-019-00921-y
3529. Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches O. Lo-Thong et al. https://doi.org/10.1038/s41598-020-70295-5
3530. An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application H. Wang et al. https://doi.org/10.5194/gmd-15-3555-2022
3531. Simulation of Renewable Energy Systems with Alternative Energy Scenarios in Turkey’s Electrical Energy Planning E. Ertane Baş et al. https://doi.org/10.3390/su17062665
3532. Dynamic Changes, Spatiotemporal Differences, and Ecological Effects of Impervious Surfaces in the Yellow River Basin, 1986–2020 J. Zhang et al. https://doi.org/10.3390/rs15010268
3533. A Generalized Linear Model and Machine Learning Approach for Predicting the Frequency and Severity of Cargo Insurance in Thailand’s Border Trade Context P. Panjee & S. Amornsawadwatana https://doi.org/10.3390/risks12020025
3534. Prediction of time-dependent concrete mechanical properties based on advanced deep learning models considering complex variables Y. Jiang et al. https://doi.org/10.1016/j.cscm.2024.e03629
3535. Parametric Analysis of a Dual-Fluid Air–Refrigerant BIPV/T Façade Concept B. Nghana et al. https://doi.org/10.3390/en19194697
3536. Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India C. Pande et al. https://doi.org/10.1016/j.envpol.2024.124040
3537. Comparative analyses of ERA-Interim and COSMO-MUSCAT simulated outputs of March 2010 dust outbreak over West Africa and its impact on climatic parameters M. Ochei https://doi.org/10.1007/s44292-026-00076-8
3538. Enhancing the Applicability of Satellite Remote Sensing for PM2.5 Estimation Using MODIS Deep Blue AOD and Land Use Regression in California, United States H. Lee et al. https://doi.org/10.1021/acs.est.6b01438
3539. Analyzing the correlation between groundwater tables and the area of Groundwater-Dependent lakes in arid region R. Zhang et al. https://doi.org/10.1016/j.ecolind.2024.111808
3540. Application of various robust techniques to study and evaluate the role of effective parameters on rock fragmentation A. Mehrdanesh et al. https://doi.org/10.1007/s00366-021-01522-4
3541. A formal evaluation of KNN and decision tree algorithms for waste generation prediction in residential projects: a comparative approach A. Gulghane et al. https://doi.org/10.1007/s42107-023-00772-5
3542. Artificial neural network based prediction of malaria abundances using big data: A knowledge capturing approach S. Thakur & R. Dharavath https://doi.org/10.1016/j.cegh.2018.03.001
3543. Evaluation of CORDEX Africa regional climate models performance in simulating climatology of Zarima sub-basin northwestern Ethiopia M. Kassahun et al. https://doi.org/10.1186/s40068-023-00325-4
3544. A Prediction Model Based on Artificial Neural Network for the Temperature Performance of a Hydrodynamic Retarder in Constant-Torque Braking Process Z. Wang et al. https://doi.org/10.1109/ACCESS.2021.3057494
3545. Spatial assessment of soil health in the Krishna Delta using machine learning and land use patterns A. Garg et al. https://doi.org/10.1007/s44378-026-00243-8
3546. Integrated Hydrological Analysis of Little Akaki Watershed Using SWAT-MODFLOW, Ethiopia M. Tolera & I. Chung https://doi.org/10.3390/app11136011
3547. Forest inventory with high-density UAV-Lidar: Machine learning approaches for predicting individual tree attributes A. Corte et al. https://doi.org/10.1016/j.compag.2020.105815
3548. The Impact of Satellite‐Derived Land Surface Temperatures on Numerical Weather Prediction Analyses and Forecasts B. Candy et al. https://doi.org/10.1002/2016JD026417
3549. The Bidirectional Gated Recurrent Unit Network Based on the Inception Module (Inception-BiGRU) Predicts the Missing Data by Well Logging Data Y. Sun et al. https://doi.org/10.1021/acsomega.3c03677
3550. An Individual Motion-Driven Artificial Intelligence Method for Precipitation Forecasting Using Radar Image Sequencing N. Yang & X. Li https://doi.org/10.1109/TGRS.2024.3439871
3551. Machine learning and Monte Carlo simulation for hybrid shielding materials F. Eki̇nci̇ et al. https://doi.org/10.1016/j.radphyschem.2026.114361
3552. Software tooling support for atmospheric dispersion modeling of the AERMOD system A. Borges et al. https://doi.org/10.1016/j.envsoft.2026.107079
3553. Investigating indoor concentrations of PM10 in an underground loading dock in Malaysia M. Abualqumboz et al. https://doi.org/10.1007/s11869-016-0413-4
3554. The first large-scale bioavailable Sr isotope map of China and its implication for provenance studies X. Wang & Z. Tang https://doi.org/10.1016/j.earscirev.2020.103353
3555. Assessing climate change impacts on maize yield and effects of mulching adaptation in Arba Minch, Ethiopia B. Reta https://doi.org/10.1007/s43621-025-01968-2
3556. Spatial Distribution and Prediction of Cu and Mn in Helan Farmland Soil Based on GIS and Machine Learning L. Ma et al. https://doi.org/10.1002/ldr.70585
3557. Optimal Configuration of Physical Process Parameterization Scheme Combination for Simulating Meteorological Variables in Weather Research and Forecasting Model: Based on Orthogonal Experimental Design and Comprehensive Evaluation Method Z. Li et al. https://doi.org/10.3390/atmos15111385
3558. Social cognitive career theory and accounting students’ intentions to pursue an auditing career C. Agyenim-Boateng et al. https://doi.org/10.1108/JAAR-05-2024-0172
3559. Design of high-temperature NiTiCuHf shape memory alloys with minimum thermal hysteresis using Bayesian optimization J. Broucek et al. https://doi.org/10.1016/j.actamat.2024.120651
3560. Integrated biophysical assessment and erosion hotspot mapping for land degradation prioritization in the Megele washa watershed, Ethiopia K. Atlaw et al. https://doi.org/10.1038/s41598-026-49658-x
3561. Synoptic-aware explainable artificial intelligence (SA-XAI) model for bias correction and regionalization of satellite precipitation over complex terrain M. Tosan et al. https://doi.org/10.1016/j.atmosres.2026.109213
3562. Mesh/membrane composite with superior mechanical performance: A deep learning-based design Y. Zhang et al. https://doi.org/10.1016/j.compscitech.2022.109735
3563. A Singh-Based Fuzzy Logic Framework for Short-Term Discharge and Flood Peak Prediction Under Data-Scarce Hydrological Conditions M. Khazaeiathar & B. Schmalz https://doi.org/10.3390/hydrology13090238
3564. Cadmium in rice grains from a field trial in relation to model parameters of Cd-toxicity and -absorption in rice seedlings W. Chiao et al. https://doi.org/10.1016/j.ecoenv.2018.11.061
3565. Maize yield prediction using machine learning: a systematic literature review J. Nyengere et al. https://doi.org/10.3389/frai.2026.1735157
3566. Pattern of air pollutants and land surface temperature in Nigeria using space-time pattern mining techniques T. Waheeb et al. https://doi.org/10.1007/s00704-026-06507-1
3567. Sales Forecasting for New Products Using Homogeneity-Based Clustering and Ensemble Method S. Hwang et al. https://doi.org/10.3390/electronics14030520
3568. GRACE Downscaling and Machine Learning Models for Groundwater Prediction: A Systematic Review M. Al Nadabi et al. https://doi.org/10.3390/hydrology13050135
3569. A webGIS Application to Assess Seawater Quality: A Case Study in a Coastal Area in the Northern Aegean Sea D. Kitsiou et al. https://doi.org/10.3390/jmse9010033
3570. Frequency analysis of extreme flows using an Artificial Neural Network (ANN) model case Western High Atlas - Morocco A. El Alaoui El Fels et al. https://doi.org/10.1007/s12145-022-00784-w
3571. Data-Driven Natural Gas Spot Price Forecasting with Least Squares Regression Boosting Algorithm M. Su et al. https://doi.org/10.3390/en12061094
3572. Prediction of Continuous Cooling Transformation Diagrams for Ni-Cr-Mo Welding Steels via Machine Learning Approaches X. Geng et al. https://doi.org/10.1007/s11837-020-04057-z
3573. SentiHawkes: a sentiment-aware Hawkes point process to model service quality of public transport using Twitter data M. Rahimi et al. https://doi.org/10.1007/s12469-022-00310-7
3574. Prediction model of the outflow temperature from stratified reservoir regulated by stratified water intake facility based on machine learning algorithm Y. Lu et al. https://doi.org/10.1016/j.ecolind.2023.110560
3575. Integration of Deep Learning and Sparrow Search Algorithms to Optimize Greenhouse Microclimate Prediction for Seedling Environment Suitability D. Shi et al. https://doi.org/10.3390/agronomy14020254
3576. Development of new delivery systems of hyaluronic acid based on silica hydrogels: In vitro kinetics of release and enzymatic degradation of the drug E. Dolinina & E. Parfenyuk https://doi.org/10.1016/j.onano.2025.100279
3577. A double-stage method for improving long-term numerical wind speed prediction via chaos-noise decoupling Z. Duan et al. https://doi.org/10.1080/15435075.2026.2698762
3578. Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks E. Sharma et al. https://doi.org/10.1109/ACCESS.2020.3039002
3579. Application of SVM Based on Optimization of Newton Raphson's Algorithm in Non‐Invasive Blood Glucose Detection Y. Wu et al. https://doi.org/10.1002/ima.70100
3580. Proceso operativo simple para el análisis de frecuencias de crecientes con series de duración parcial D. Campos-Aranda https://doi.org/10.24850/j-tyca-2025-03-07
3581. Climate change impacts on potential evapotranspiration and crop water demand in the Tana Subbasin, upper blue Nile Basin, Ethiopia H. Eshetie et al. https://doi.org/10.2166/wcc.2026.023
3582. Assessment of the Spatiotemporal Dynamics of Agricultural Drought in the Tekeze Watershed, Northern Ethiopia Y. Tela et al. https://doi.org/10.1002/joc.70016
3583. Greening the arid: the impact of urban vegetation on the outdoor thermal comfort in hot and dry city F. Meliouh et al. https://doi.org/10.46932/sfjdv5n12-005
3584. Advancing Mineral Exploration: Robust and Interpretable Carbonate Quantification in Drill Cores via Hyperspectral Machine Learning V. Sales et al. https://doi.org/10.3390/min16050479
3585. A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification T. Ju et al. https://doi.org/10.1007/s11783-023-1608-1
3586. Investigating the Inductive Bias of Visual Convolutional Backbones for Multi-Step Photovoltaic Forecasting: A ConvNeXt–LSTM Approach B. Lv et al. https://doi.org/10.3390/en19102264
3587. Numerical study of ceiling fan-assisted cooling for sleep thermal comfort in hot-humid climates S. Yasmeen et al. https://doi.org/10.1016/j.applthermaleng.2026.131310
3588. Satellite thermographies as an essential tool for the identification of cold air pools: an example from SE Spain D. Espín Sánchez et al. https://doi.org/10.1080/22797254.2022.2133744
3589. Predicting soil hydraulic conductivity using stacked deep neural networks: Long-term tillage impacts on a Vertisol in the Eastern Mediterranean İ. Çelik et al. https://doi.org/10.1016/j.still.2025.106797
3590. Sales Prediction Based on Machine Learning Scenarios Q. Mao https://doi.org/10.54691/bcpbm.v23i.1474
3591. The development of evolutionary computing model for simulating reference evapotranspiration over Peninsular Malaysia M. Muhammad et al. https://doi.org/10.1007/s00704-021-03606-z
3592. A framework to compare the performance of spatial disaggregation methods of statistical climate downscaling in South America C. Aboitiz et al. https://doi.org/10.1016/j.ejrh.2026.103834
3593. Predictive validation of an extended TPB model in Islamic branding: PLSpredict and CVPAT evidence from Muslim and non-Muslim Thai consumers Z. Jumani https://doi.org/10.1108/JIMA-09-2025-0574
3594. Thermographic images for predicting the weight of lamb cuts M. de Souza et al. https://doi.org/10.1071/AN25213
3595. From Transcripts to Insights for Recommending the Curriculum to University Students T. Mai et al. https://doi.org/10.1007/s42979-020-00332-7
3596. Machine Learning-Based Estimation of Sewage Treatment Facility Capacity and Design Adequacy: A Case Study in Korea J. Lee et al. https://doi.org/10.3390/pr13123995
3597. Investigating the Techno-economic Utility of Integrating an Optimized PV/diesel Hybrid System in an Entire Oil Field in the Western-dessert in Egypt M. El-Yamany et al. https://doi.org/10.37394/232016.2021.16.11
3598. A network percolation-based contagion model of flood propagation and recession in urban road networks C. Fan et al. https://doi.org/10.1038/s41598-020-70524-x
3599. Predicting odor concentration for environmental sustainability: a comparison among machine Learning methods M. Palma et al. https://doi.org/10.1007/s11135-025-02056-3
3600. Building a skeleton-based 3D body model with angle sensor data Q. Wang et al. https://doi.org/10.1016/j.smhl.2020.100141
3601. On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression J. Qi et al. https://doi.org/10.1109/LSP.2020.3016837
3602. Wind damage drivers and forest owners’ attitudes towards development of a decision support system for Norwegian forestry J. Seuren et al. https://doi.org/10.1080/02827581.2026.2688148
3603. Multi-objective optimization ensembled generative design for large-diameter tunnel passing underneath existing tunnels P. Lin et al. https://doi.org/10.1016/j.asoc.2023.110448
3604. From Aerosol Optical Depth to Risk Assessment: A Novel Framework for Environmental Impact Statistics of Air Quality Using AERONET I. Tanasa et al. https://doi.org/10.3390/environments12080285
3605. Digitalization of Legacy Datasets and Machine Learning Regression Yields Insights for Reservoir Property Prediction and Submarine-Fan Evolution: A Subsurface Example From the Lewis Shale, Wyoming T. Martin et al. https://doi.org/10.2110/001c.36638
3606. Refining Preference-Based Recommendation with Associative Rules and Process Mining Using Correlation Distance M. Bin Ahmadon et al. https://doi.org/10.3390/bdcc7010034
3607. Support Vector Regression Prediction of Dye Saturation in Recycled PET/PCT Microfibers for Deep Black Shade H. Cho et al. https://doi.org/10.1007/s12221-025-01285-5
3608. Biological nitrogen fixation across major biomes in Latin America: Patterns and global change effects C. Reis et al. https://doi.org/10.1016/j.scitotenv.2020.140998
3609. Opt-TCAE: Optimal temporal convolutional auto-encoder for boiler tube leakage detection in a thermal power plant using multi-sensor data H. Kim et al. https://doi.org/10.1016/j.eswa.2022.119377
3610. Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model Z. Yaseen et al. https://doi.org/10.1016/j.jhydrol.2017.09.007
3611. Design and Development of a New Methodology Based on Expert Systems Applied to the Prevention of Indoor Radon Gas Exposition Risks J. Cerqueiro-Pequeño et al. https://doi.org/10.3390/ijerph18010269
3612. A New Method for Feature Extraction and Classification of Single-Stranded DNA Based on Collaborative Filter B. Yan et al. https://doi.org/10.1155/2020/3876367
3613. Machine learning in ARDS: an intensivist’s guide to artificial intelligence applications R. Lombardi et al. https://doi.org/10.1186/s13054-026-05928-8
3614. Analysis of Changes in Hydrodynamics Patterns and Sedimentation due to Coastal Reclamation Plans in Surabaya A. Wijaya & C. De Silva Nusantara https://doi.org/10.1088/1755-1315/1551/1/012063
3615. Prediction of Precipitation Based on Recurrent Neural Networks in Jingdezhen, Jiangxi Province, China J. Kang et al. https://doi.org/10.3390/atmos11030246
3616. Revolutionizing nano-optics: How artificial intelligence is shaping the next frontier of scanning near-field optical microscopy Z. Jin et al. https://doi.org/10.1063/5.0320251
3617. Optimization and kinetic modeling of media composition for hyaluronic acid production from carob extract with Streptococcus zooepidemicus A. Ozcan et al. https://doi.org/10.1007/s00449-022-02806-9
3618. Predicting Yield Losses in Rice Mixed-Weed Species Infestations in California W. Brim-DeForest et al. https://doi.org/10.1614/WS-D-16-00079.1
3619. Machine acceleration time series prediction for dimensional accuracy of 3D printed parts J. Deb et al. https://doi.org/10.1016/j.dsm.2024.02.002
3620. Parameter Extraction Method of Overlapping Radar Signals Using Modulation Recognition-Guided Semantic Segmentation W. Huo et al. https://doi.org/10.1109/JSTARS.2024.3361905
3621. Investigating the Accuracy of Forecasting Travel Duration for Uber Trips and Analyzing the Influence of Weather on Traffic Flow S. Mewada et al. https://doi.org/10.32628/CSEIT2139028
3622. Prediction of Length of Stay on the Intensive Care Unit Based on Bayesian Neural Network J. Fang et al. https://doi.org/10.1088/1742-6596/1631/1/012089
3623. Estimation of syngas yield in hydrothermal gasification process by application of artificial intelligence models Y. Ayub et al. https://doi.org/10.1016/j.renene.2023.118953
3624. Explainable ensemble machine learning algorithms for predicting wind speed by incorporating Shapley additive explanations R. Gupta et al. https://doi.org/10.1016/j.fraope.2026.100781
3625. Global Completion of Occupancy Maps Using Generative Models S. GUZEL & E. Uslu https://doi.org/10.5565/rev/elcvia.2162
3626. Pilot study: validity and reliability of textile insoles used to measure the characteristics of landing tasks during rehabilitation and artistic gymnastics D. Schümperlin et al. https://doi.org/10.1186/s13104-023-06328-9
3627. Using skeletal position to estimate human error rates in telemanipulator operators T. Piercy et al. https://doi.org/10.3389/frobt.2023.1287417
3628. Impact of spaceborne carbon monoxide observations from the S-5P platform on tropospheric composition analyses and forecasts R. Abida et al. https://doi.org/10.5194/acp-17-1081-2017
3629. Automated Machine Learning for High-Resolution Daily and Hourly Methane Emission Mapping for Rice Paddies over South Korea: Integrating MODIS, ERA5-Land, and Soil Data J. Jang et al. https://doi.org/10.3390/rs18050753
3630. Hybrid application of response surface methodology modelling and machine learning exploratory prediction for reducing sugar recovery from potato peel waste for bioethanol production I. Sanusi et al. https://doi.org/10.1016/j.nxcen.2026.100113
3631. Data refinement for enhanced ionic conductivity prediction in garnet-type solid-state electrolytes Z. Kharbouch et al. https://doi.org/10.1016/j.ssi.2024.116713
3632. Anomalous events removal for automated traffic noise maps generation R. Alsina-Pagès et al. https://doi.org/10.1016/j.apacoust.2019.03.007
3633. CORTISOL HORMONE AND STRESS LEVELS: COLORIMETRIC ASSESSMENT WITH ARTIFICIAL INTELLIGENCE SUPPORTED IMAGE PROCESSING METHOD M. Çapan et al. https://doi.org/10.36306/konjes.1633932
3634. Hybrid machine learning approach in forecasting renewable energy production: Extra trees, catBoost and LightGBM based stacking model Z. Colak https://doi.org/10.1016/j.renene.2025.125167
3635. Comparative analysis of methods and model prediction performance evaluation for continuous online non-invasive quality assessment during drying of apples from two cultivars L. Shrestha et al. https://doi.org/10.1016/j.tsep.2019.100461
3636. Traffic assessments and economic outcomes: real-time optimization through digital twins and machine learning Z. Rezaei et al. https://doi.org/10.1007/s41062-025-02380-5
3637. Optimal feature-based InSAR phase filtering framework using convolutional neural network and mathematical morphology M. Hamid et al. https://doi.org/10.1016/j.ejrs.2026.01.001
3638. Comparing minimalist and comprehensive IMU-based approaches for monitoring horse rider posture A. Louis et al. https://doi.org/10.1177/17543371261453483
3639. Detecting Anomalies in Meteorological Data Using Support Vector Regression M. Lee et al. https://doi.org/10.1155/2018/5439256
3640. One‐ to 10‐Day Forecasts of Ionospheric Total Electron Content Using a Statistical Model J. Lean https://doi.org/10.1029/2018SW002077
3641. Análisis de frecuencias de crecientes trivariados con dependencia regional y funciones Cópula D. Campos-Aranda https://doi.org/10.24850/j-tyca-2025-01-08
3642. A cross-language and cross-cultural validation of the parents' evaluation of aural/oral performance of children plus (PEACH+) rating scale in Singaporean children L. Yong Sheng et al. https://doi.org/10.1080/2050571X.2026.2697916
3643. Use of PMMA/(rice husk ash)/polypyrrole membranes for the removal of dyes and heavy metal ions H. da Rocha et al. https://doi.org/10.1016/j.jtice.2020.03.003
3644. Attitude estimation and control based on modified unscented Kalman filter for gyro-less satellite with faulty sensors S. Pourtakdoust et al. https://doi.org/10.1016/j.actaastro.2021.11.008
3645. Goodness-of-fit criteria for hydrological models: Model calibration and performance assessment D. Althoff & L. Rodrigues https://doi.org/10.1016/j.jhydrol.2021.126674
3646. Predicting precipitation based on copula-statistical models (Case study: Northwest of Iran) M. Kouhi & M. Amini https://doi.org/10.1016/j.ejrh.2025.102851
3647. Application of Machine Learning Methods to Predicting the Degree of Crystallinity of MFI Type Zeolites A. Nikiforov et al. https://doi.org/10.1134/S0965544122030057
3648. ATT-CR: Adaptive Triangular Transformer for Cloud Removal Y. Wu et al. https://doi.org/10.1109/JSTARS.2025.3596856
3649. Exploring the Influence of Climate Change on Earthen Embankments with Expansive Soil D. Ghosh et al. https://doi.org/10.3390/geosciences14020037
3650. Accurate Strain Extraction via Kernel Extreme Learning Machine for Fiber Bragg Grating Sensor X. Xu et al. https://doi.org/10.1109/JSEN.2022.3156595
3651. Geometrical Evaluation of an Overtopping Wave Energy Converter Device Subject to Realistic Irregular Waves and Representative Regular Waves of the Sea State That Occurred in Rio Grande—RS M. Paiva et al. https://doi.org/10.3390/pr13020335
3652. Dynamic Compression Response and Optimization of Stretching–Bending Synergistic Lattices at High Strain Rates X. Gao & L. Long https://doi.org/10.3390/ma19050859
3653. An integrated experimental–computational framework for optimizing SLA 3D printing parameters via machine learning and genetic algorithms A. Khan et al. https://doi.org/10.1016/j.jmrt.2026.03.133
3654. Baseline-Conditioned Spatial Heterogeneity in Ensemble-Learning Correction for Global Hourly Sea-Level Reconstruction Y. Hao et al. https://doi.org/10.3390/jmse14080697
3655. Complete-arch accuracy of seven intraoral scanners measured by the virtual-fit method D. Borbola et al. https://doi.org/10.1016/j.jdent.2024.105281
3656. Mechanical and microstructural properties of broadband anti-reflective TiO2/SiO2 coatings for photovoltaic applications fabricated by magnetron sputtering D. Zambrano et al. https://doi.org/10.1016/j.solmat.2020.110841
3657. Forecasting lake evaporation under a changing climate with an integrated artificial neural network model: A case study Lake Nasser, Egypt M. El-Mahdy et al. https://doi.org/10.1016/j.jafrearsci.2021.104191
3658. Prediction of site-specific drug deposition via dry powder inhaler using non-invasive real-time particle emission signal monitoring system S. Hatazoe et al. https://doi.org/10.3389/fphar.2026.1774142
3659. Validation of Unmanned Surface Vehicle-Based Multibeam Echosounder Bathymetric Surveys: Comparison with Manned Platforms in Harbor and Island Areas J. Bae et al. https://doi.org/10.7780/kjrs.2025.41.6.2
3660. Estimating 2-year flood flows using the generalized structure of the Group Method of Data Handling R. Walton et al. https://doi.org/10.1016/j.jhydrol.2019.05.068
3661. Biomass estimation of Sonneratia caseolaris (l.) Engler at a coastal area of Hai Phong city (Vietnam) using ALOS-2 PALSAR imagery and GIS-based multi-layer perceptron neural networks T. Pham et al. https://doi.org/10.1080/15481603.2016.1269869
3662. Climate-adaptive passive design for sustainable libraries: simulation and machine learning-based multi-objective optimisation of comfort, energy, and environmental performance G. Izmir Tunahan & G. Özer Yaman https://doi.org/10.3389/fbuil.2026.1783466
3663. Measurement and modeling of particulate matter concentrations: Applying spatial analysis and regression techniques to assess air quality S. Sajjadi et al. https://doi.org/10.1016/j.mex.2017.09.006
3664. Enhancing Nickel Recovery from Laterite Ores via High-Pressure Acid Leaching: Machine Learning and Design of Experiments for Process Optimization and Environmental Sustainability B. Surya et al. https://doi.org/10.1007/s40831-025-01290-1
3665. Ensemble learning for predicting mortality rates affected by air quality K. Dewi et al. https://doi.org/10.1088/1742-6596/1192/1/012021
3666. Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain G. Zhang et al. https://doi.org/10.3390/s21010046
3667. Development of a surrogate model of an amine scrubbing digital twin using machine learning methods A. Galeazzi et al. https://doi.org/10.1016/j.compchemeng.2023.108252
3668. New Modeling Approach for Predicting Disaggregated Time-Series Traffic Crashes B. Cai et al. https://doi.org/10.1177/03611981231182703
3669. CORTO: The Celestial Object Rendering TOol at DART Lab M. Pugliatti et al. https://doi.org/10.3390/s23239595
3670. Impacts of DEM type and resolution on deep learning-based flood inundation mapping M. Fereshtehpour et al. https://doi.org/10.1007/s12145-024-01239-0
3671. Thermal pressure ventilation analysis in a sloping high-temperature tunnel: A case study in China J. Che et al. https://doi.org/10.1016/j.tust.2024.106183
3672. A Comparative Study on Classification Methods for Renal Cell and Lung Cancers Using RNA-Seq Data B. Haznedar & N. Simsek https://doi.org/10.1109/ACCESS.2022.3211505
3673. Effect of urban environment on cardiovascular health: a feasibility pilot study using machine learning to predict heart rate variability in patients with heart failure V. van Es et al. https://doi.org/10.1093/ehjdh/ztae050
3674. A Practical Design and Implementation of a Low Cost Platform for Remote Monitoring of Lower Limb Health of Amputees in the Developing World N. Mathur et al. https://doi.org/10.1109/ACCESS.2016.2622163
3675. Shield machine position prediction and anomaly detection during tunnelling in loess region using ensemble and deep learning algorithms X. Bai et al. https://doi.org/10.1007/s11440-023-01902-8
3676. Design principles and emerging advances of high-entropy alloy electrocatalysts for hydrogen evolution X. Zhao et al. https://doi.org/10.1016/j.ijhydene.2026.154241
3677. Reconstruction of Meteorological Records by Methods Based on Dimension Reduction of the Predictor Dataset C. Balsa et al. https://doi.org/10.3390/computation11050098
3678. Mathematical modeling of batch bioethanol generation from carob extract in the suspended‐cell stirred‐tank bioreactor M. Germec et al. https://doi.org/10.1002/er.5612
3679. Synthetic CT for gamma knife radiosurgery dose calculation: A feasibility study F. Li et al. https://doi.org/10.1016/j.ejmp.2024.104504
3680. Column-wise Guided Data Imputation A. Petrozziello & I. Jordanov https://doi.org/10.1016/j.procs.2017.05.008
3681. Pose2Sim: An End-to-End Workflow for 3D Markerless Sports Kinematics—Part 1: Robustness D. Pagnon et al. https://doi.org/10.3390/s21196530
3682. Machine learning + microwave pyrolysis: Optimal design for the collaborative preparation of hydrogen production with ceramsite X. Song & S. Luo https://doi.org/10.1016/j.ijhydene.2025.151629
3683. Analysis of intensity and spatial patterns of public use in natural treatment systems using geotagged photos from social media A. Ghermandi https://doi.org/10.1016/j.watres.2016.09.009
3684. Coupling of 1D models (SWAT and SWMM) with 2D model (iRIC) for mapping inundation in Brahmani and Baitarani river delta P. Rai et al. https://doi.org/10.1007/s11069-018-3281-4
3685. Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan, China H. Zhang et al. https://doi.org/10.1080/10962247.2017.1292968
3686. Australia's terrestrial industrial footprint and ecological intactness R. Venegas-Li et al. https://doi.org/10.5194/essd-18-2179-2026
3687. Meteorological Variables’ Influence on Electric Power Generation for Photovoltaic Systems Located at Different Geographical Zones in Mexico J. Ruz-Hernandez et al. https://doi.org/10.3390/app9081649
3688. Physics-informed machine learning enabled virtual experimentation for 3D printed thermoplastic Z. Chen et al. https://doi.org/10.1039/D4MH01022A
3689. Using Dual Beta Distributions to Create “Proper” ROC Curves Based on Rating Category Data D. Mossman & H. Peng https://doi.org/10.1177/0272989X15582210
3690. Election Algorithm for Random k Satisfiability in the Hopfield Neural Network S. Sathasivam et al. https://doi.org/10.3390/pr8050568
3691. A Multistage Hybrid Deep Learning Model for Enhanced Solar Tracking M. Mulenga et al. https://doi.org/10.1109/ACCESS.2023.3333895
3692. Artificial intelligence for hospitality big data analytics: developing a prediction model of restaurant review helpfulness for customer decision-making M. Lee et al. https://doi.org/10.1108/IJCHM-06-2020-0587
3693. Thermo-energetic performance of two dwellings during a heat wave in the Buenos Aires province, Argentina: On-site response assessment and adaptation strategies testing P. Chévez https://doi.org/10.1177/1420326X241301512
3694. High-speed railway seismic response prediction using CNN-LSTM hybrid neural network X. Zhang et al. https://doi.org/10.1007/s13349-023-00758-6
3695. Application of data prediction models in a real water supply network: comparison between arima and artificial neural networks A. Silva et al. https://doi.org/10.1590/2318-0331.292420230057
3696. Improved Prediction of Harmful Algal Blooms in Four Major South Korea’s Rivers Using Deep Learning Models S. Lee & D. Lee https://doi.org/10.3390/ijerph15071322
3697. FGC-E-Nose and HS-SPME/GC–MS Comparative Analysis of Headspace Volatiles: Hibiscus Leaves Application S. Adusumilli et al. https://doi.org/10.1021/acsfoodscitech.6c00142
3698. Three-dimensional Reverse Modeling and Hydraulic Analysis of the Intake Structure of Pumping Stations on Sediment-laden Rivers C. Xu et al. https://doi.org/10.1007/s11269-022-03385-w
3699. Bioconversion of wheat bran into high value-added products and modelling of fermentations M. Germec et al. https://doi.org/10.1016/j.indcrop.2019.111565
3700. Potential applications of artificial intelligence in photocatalysis performance enhancement: a review A. Ibrahim et al. https://doi.org/10.1016/j.jphotochem.2026.117526
3701. Predicting nanoscale stress-strain curves: A Gaussian processes within a Bayesian framework A. Altarabsheh et al. https://doi.org/10.1016/j.ijsolstr.2025.113438
3702. Tracking Quarter-Century Spatio-Temporal Soil Salinization Dynamics in Semi-Arid Landscapes Using Earth Observation and Machine Learning A. Achemrk et al. https://doi.org/10.3390/rs18050687
3703. Merging radar and in situ rainfall measurements: An assessment of different combination algorithms M. Hasan et al. https://doi.org/10.1002/2015WR018441
3704. A combined application of advanced statistical, soft computing and least square methods for the prediction of higher heating value of coal A. Lawal et al. https://doi.org/10.1080/19392699.2025.2593959
3705. Polyp segmentation with distraction separation T. Liu et al. https://doi.org/10.1016/j.eswa.2023.120434
3706. Predicting return-to-work outcomes: A comparative analysis of logistic regression and machine learning in occupational mental health A. Dias et al. https://doi.org/10.1097/MD.0000000000049825
3707. Machine Learning-Based Water Level Forecast in a Dam Reservoir: A Case Study of Karaçomak Dam in the Kızılırmak Basin, Türkiye S. Güneş Şen https://doi.org/10.3390/su17188378
3708. Enhancing the performance of 1D–2D flood models using satellite laser altimetry and multi-mission surface water extent maps from Earth observation (EO) data T. Charoensuk et al. https://doi.org/10.5194/hess-29-5065-2025
3709. Predicting mechanical properties of defective h-BN nanosheets using Data-Driven models S. Mousavi & A. Montazeri https://doi.org/10.1016/j.commatsci.2023.112380
3710. Monitoring wood phenology using dendrometers: opportunities and pitfalls I. Adikurnia & C. Rathgeber https://doi.org/10.1017/qpb.2025.10031
3711. Design and implementation of a hybrid MLP-GSA model with multi-layer perceptron-gravitational search algorithm for monthly lake water level forecasting M. Ghorbani et al. https://doi.org/10.1007/s00477-018-1630-1
3712. Application of QSAR models for acute toxicity of tetrazole compounds administrated orally and intraperitoneally in rat and mouse Z. Liu et al. https://doi.org/10.1016/j.tox.2023.153679
3713. Spatiotemporal Prediction of Landslide Displacement Using Graph Convolutional Network-Based Models: A Case Study of the Tangjiao 1# Landslide in Chongqing, China Y. Sun et al. https://doi.org/10.3390/app14209288
3714. Estimating Canopy Isoprene Concentrations over a Deciduous Dipterocarp Forest in Northern Thailand Using a Calibrated Box Model and Physics-Informed Machine Learning: A Pilot Study A. Phaichot et al. https://doi.org/10.3390/atmos17090809
3715. Comparative Analysis of Machine Learning Techniques for Predicting Air Quality in Smart Cities S. Ameer et al. https://doi.org/10.1109/ACCESS.2019.2925082
3716. Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia S. Lopez-Restrepo et al. https://doi.org/10.3390/atmos12010091
3717. Machine Learning and Artificial Intelligence in Surgical Research S. Srinivas & A. Young https://doi.org/10.1016/j.suc.2022.11.002
3718. Stage-specific alignment between operational loss and rear-end conflict exposure during traffic oscillations Y. Zhou et al. https://doi.org/10.1080/15389588.2026.2736801
3719. Groundwater level predictions in the Thames Basin, London over extended horizons using Transformers and advanced machine learning models A. Ali et al. https://doi.org/10.1016/j.jclepro.2024.144300
3720. What drives precious metals pricing? An explainable Mixed-frequency machine learning approach X. Wang et al. https://doi.org/10.1007/s13563-025-00586-8
3721. Flow parameter estimation using laser absorption spectroscopy and approximate Bayesian computation J. Christopher et al. https://doi.org/10.1007/s00348-020-03122-2
3722. Privileged structure-based molecular fingerprints for organic electronic materials: towards intuitive machine learning interpretation T. Yang et al. https://doi.org/10.1186/s13321-026-01169-7
3723. Methods of In Situ Assessment of Infiltration Rate Reduction in Groundwater Recharge Basins F. Barquero et al. https://doi.org/10.3390/w11040784
3724. Goal or Miss? A Bernoulli Distribution for In-Game Outcome Prediction in Soccer W. Yao et al. https://doi.org/10.3390/e24070971
3725. Remaining useful life prediction using sequential metaheuristic optimization of stacked-LSTM hyperparameters A. Yilma et al. https://doi.org/10.1016/j.cherd.2026.03.009
3726. GMDH-HS hybrid framework for optimization of combined drought indices in arid ecosystems N. Shahbeygi et al. https://doi.org/10.1016/j.asej.2026.104268
3727. NNKcat: deep neural network to predict catalytic constants (Kcat) by integrating protein sequence and substrate structure with enhanced data imbalance handling J. Zhai et al. https://doi.org/10.1093/bib/bbaf212
3728. Added value of an atmospheric circulation pattern‐based statistical downscaling approach for daily precipitation distributions in complex terrain B. Böker et al. https://doi.org/10.1002/joc.8136
3729. Impact Analysis of Univariate and Multivariate Bias Correction on Rice Irrigation Water Needs in Jiangxi Province, China W. Hanggoro et al. https://doi.org/10.3390/w12020381
3730. An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index M. Ali et al. https://doi.org/10.1016/j.atmosres.2018.02.024
3731. Marvel: Towards Efficient Federated Learning on IoT Devices L. Liu & X. Xu https://doi.org/10.1016/j.comnet.2024.110375
3732. Optimal Temporal Filtering of the Cosmic-Ray Neutron Signal to Reduce Soil Moisture Uncertainty P. Davies et al. https://doi.org/10.3390/s22239143
3733. Modeling Sulfate Reduction Using Ethanol as an Electron Donor in an Anaerobic Sequencing Batch Biofilm Reactor J. Carvalho et al. https://doi.org/10.1061/JOEEDU.EEENG-8038
3734. Hydrological Model Calibration in Data-Scarce Mediterranean Catchments: A Comparative Assessment of Three Strategies A. Jahanshahi et al. https://doi.org/10.3390/hydrology13020066
3735. Development and Application of a Multi-Objective Tool for Thermal Design of Heat Exchangers Using Neural Networks J. de Andrés Honrubia et al. https://doi.org/10.3390/math9101120
3736. Material Flow Analysis for Demand Forecasting and Lifetime-Based Inflow in Indonesia’s Plastic Bag Supply Chain E. Octaviani et al. https://doi.org/10.3390/logistics9030105
3737. State Parameter Based Liquefaction Probability Evaluation K. Kumar et al. https://doi.org/10.1007/s40891-023-00495-2
3738. Modern Artificial Intelligence Model Development for Undergraduate Student Performance Prediction: An Investigation on Engineering Mathematics Courses R. Deo et al. https://doi.org/10.1109/ACCESS.2020.3010938
3739. A Systematic Review of Applications of Machine Learning and Other Soft Computing Techniques for the Diagnosis of Tropical Diseases K. Attai et al. https://doi.org/10.3390/tropicalmed7120398
3740. Analyzing the compressive strength of green fly ash based geopolymer concrete using experiment and machine learning approaches K. Nguyen et al. https://doi.org/10.1016/j.conbuildmat.2020.118581
3741. Calibration and validation of the AquaCrop model for open-field tomato water-nitrogen management in dry-hot valleys M. Cheng et al. https://doi.org/10.1016/j.indcrop.2026.124036
3742. Remotely Sensed Boro Rice Production Forecasting Using MODIS-NDVI: A Bangladesh Perspective B. Faisal et al. https://doi.org/10.3390/agriengineering1030027
3743. The Comparison of the ANN and SVM Methods for the Prediction of Voltage Drop on a Subway Line i. KOCAARSLAN et al. https://doi.org/10.29137/umagd.352946
3744. Imaging time-series with features to enable visual recognition of regional energy consumption by bio-inspired optimization of deep learning J. Chou et al. https://doi.org/10.1016/j.energy.2021.120100
3745. Deep learning in fringe projection: A review H. Liu et al. https://doi.org/10.1016/j.neucom.2024.127493
3746. Forecasting water level of Glacial fed perennial river using a genetically optimized hybrid Machine learning model M. Imran et al. https://doi.org/10.1016/j.matpr.2021.02.256
3747. Assessment of Feldkamp-Davis-Kress Reconstruction Parameters in Overall Image Quality in Cone Beam Computed Tomography H. Kim et al. https://doi.org/10.3390/app14167058
3748. Low-Illumination Image Enhancement Based on Deep Learning Techniques: A Brief Review H. Tang et al. https://doi.org/10.3390/photonics10020198
3749. Comparison of microwave moisture evaluation quality in time and frequency domain Z. Suchorab et al. https://doi.org/10.1088/1742-6596/2628/1/012027
3750. Analysis of the Post-Cyclonic Physical Flood Susceptibility and Changes of Mangrove Forest Area Using Multi-Criteria Decision-Making Process and Geospatial Analysis in Indian Sundarbans B. Mondal et al. https://doi.org/10.3390/atmos15040432
3751. Gait evaluation using inertial measurement units in subjects with Parkinson’s disease M. Zago et al. https://doi.org/10.1016/j.jelekin.2018.06.009
3752. Crowdsourcing Based Performance Analysis of Mobile User Heterogeneous Services L. Amour & A. Dandoush https://doi.org/10.3390/electronics11071011
3753. On the Efficacy of ARFIMA, ARTFIMA, and MARFIMA Models in Forecasting Nigerian Crude Oil Prices M. Tasi’u et al. https://doi.org/10.56919/usci.2543.021
3754. Nutrient distribution mapping model of the Bera River basin in Saleh Bay, West Nusa Tenggara A. Rahman et al. https://doi.org/10.1051/bioconf/202622006010
3755. A Knowledge-Aided Robust Ensemble Kalman Filter Algorithm for Non-Linear and Non-Gaussian Large Systems S. Lopez-Restrepo et al. https://doi.org/10.3389/fams.2022.830116
3756. Adaptive noise-aware denoising network: Effective denoising for CT images with varying noise intensity H. Jin et al. https://doi.org/10.1016/j.bspc.2024.106548
3757. Participants sample generation based on association rules and data imputation in vertical federated learning X. Liu et al. https://doi.org/10.1016/j.eswa.2026.132049
3758. Bitcoin monthly return forecast: A comparison of ARIMA and multi layer Perceptron Artificial Neural Network I. Lazović et al. https://doi.org/10.5937/intrev2302163L
3759. Predicting the performance of an industrial furnace using Gaussian process and linear regression: A comparison A. Galeazzi et al. https://doi.org/10.1016/j.compchemeng.2023.108513
3760. Evaluation of Wind Energy Potential of Bolu Province Using Weibull Distribution B. Erdogan et al. https://doi.org/10.31466/kfbd.1755266
3761. Systemic multi-scale approaches to predict the flowability at various temperature and mechanical properties of cement paste modified with nano-calcium carbonate A. Salih et al. https://doi.org/10.1016/j.conbuildmat.2020.120777
3762. First report on exploration of structural features of natural compounds (NPACT database) for anti-breast cancer activity (MCF-7): QSAR-based virtual screening, molecular docking, ADMET, MD simulation, and DFT studies L. Banjare et al. https://doi.org/10.1007/s40203-024-00266-5
3763. Explainable drug sensitivity prediction through cancer pathway enrichment Y. Tang & A. Gottlieb https://doi.org/10.1038/s41598-021-82612-7
3764. Monitoring versus prediction of the power of three different PV technologies in the coast of Lima-Peru B. Calsi et al. https://doi.org/10.1088/1742-6596/1841/1/012001
3765. AI-assisted knowledge assessment techniques for adaptive learning environments . Sein Minn https://doi.org/10.1016/j.caeai.2022.100050
3766. Integrated application of multiple indicators and geographic information system-based approaches for comprehensive assessment of environmental impacts of toxic metals-contaminated agricultural soils and vegetables S. Enjavinejad et al. https://doi.org/10.1016/j.scitotenv.2024.171747
3767. The influence weather station location on feedlot microclimate monitoring and its impact on heat load monitoring in Australian feedlots A. Lees et al. https://doi.org/10.1016/j.jenvman.2026.128619
3768. Prediction of Mechanical Properties of the 2024 Aluminum Alloy by Using Machine Learning Methods H. Varol Özkavak et al. https://doi.org/10.1007/s13369-022-07009-8
3769. A New Method for Estimating Groundwater Changes Based on Optimized Deep Learning Models—A Case Study of Baiquan Spring Domain in China J. Zhang et al. https://doi.org/10.3390/w15234129
3770. Multitasking While Driving: Central Bottleneck or Problem State Interference? M. Held et al. https://doi.org/10.1177/00187208221143857
3771. A machine learning approach to study randomness in enhanced tensile properties of KOH-treated jute fabric R. Basak et al. https://doi.org/10.1016/j.matpr.2023.02.088
3772. Estimating ML-driven compressive strength of geo-polymer stabilized soils R. Murtaza et al. https://doi.org/10.1007/s44290-026-00524-9
3773. The importance of good practices and false hits for QSAR-driven virtual screening real application: a SARS-CoV-2 main protease (Mpro) case study M. Serafim et al. https://doi.org/10.3389/fddsv.2023.1237655
3774. Real-time 3D US–CT fusion-based semi-automatic puncture robot system: clinical evaluation M. Nakayama et al. https://doi.org/10.1007/s11548-025-03489-9
3775. Streamlining Industrial Robot Maintenance: An Intelligent Voice Query Approach for Enhanced Efficiency Z. Ren et al. https://doi.org/10.1109/ACCESS.2024.3452269
3776. Prediction of monthly groundwater level using a new hybrid intelligent approach in the Tabriz plain, Iran E. Mirzania et al. https://doi.org/10.1007/s00521-024-09681-3
3777. Evaluation of Carbon Sequestration of Restored Degraded Lakeside Wetlands Around Chaohu Lake Based on GIS and Machine Learning Z. Wang et al. https://doi.org/10.3390/su18147159
3778. Photovoltaic Power Prediction Based on NRS-PCC Feature Selection and Multi-Scale CNN-LSTM Network J. Ma et al. https://doi.org/10.4018/IJWSR.353899
3779. Análisis de frecuencias de crecientes trivariado (Q, V, D) a través de funciones Cópula D. Campos-Aranda https://doi.org/10.24850/j-tyca-2024-05-02
3780. Probabilistic spatiotemporal solar irradiation forecasting using deep ensembles convolutional shared weight long short-term memory network G. Liu et al. https://doi.org/10.1016/j.apenergy.2021.117379
3781. Estimating Yield Components, Limiting Factors, and Yield Gaps of Enset in Ethiopia Using Easily Measurable Above-Ground Plant Traits Z. Yemataw et al. https://doi.org/10.3390/su132313255
3782. Crustal and lithospheric mantle structure below the Indian shield based on 3-D constrained gravity inversion and Deep Neural Network approach: Geological implications S. Sathapathy & M. Radhakrishna https://doi.org/10.1016/j.tecto.2023.229990
3783. Modeling the volatility of Asian REIT markets W. Loo et al. https://doi.org/10.1080/14445921.2016.1235757
3784. Smart automated anti-collision system for real-time 3D Hazard awareness in tower crane operations A. Ali et al. https://doi.org/10.1016/j.autcon.2026.107131
3785. An Assessment of the Reliability of the NIGNET Data E. Ayodele et al. https://doi.org/10.36263/nijest.2019.01.0097
3786. Geothermal reservoir temperature prediction using hydrogeochemical data of Northern Morocco: A machine learning approach F. Haffou et al. https://doi.org/10.1016/j.geothermics.2025.103259
3787. Comparative Analysis of Machine Learning Models for Prediction of Langelier Saturation Index in Groundwater of a River Basin J. Vesković et al. https://doi.org/10.3390/suschem7010007
3788. Multi-Model Evaluation of Meteorological Drivers, Air Pollutants and Quantification of Emission Sources over the Upper Brahmaputra Basin A. Saikia et al. https://doi.org/10.3390/atmos10110703
3789. Spatio-temporal analysis and forecasting of drought in the plains of northwestern Algeria using the standardized precipitation index K. Achour et al. https://doi.org/10.1007/s12040-019-1306-3
3790. Fitting the variogram model of nickel laterite using root means square error in Morowali, Central Sulawesi B. Anggara et al. https://doi.org/10.1088/1755-1315/882/1/012042
3791. A new spatial modeling and interpolation approach for high-resolution temperature maps combining reanalysis data and ground measurements M. Viggiano et al. https://doi.org/10.1016/j.agrformet.2019.05.021
3792. Clean and accurate soil quality monitoring in mining areas under environmental rehabilitation in the Eastern Brazilian Amazon D. dos Santos et al. https://doi.org/10.1007/s10661-024-12495-4
3793. Assessment of Seasonal Soil Moisture Forecasts over Southern South America with Emphasis on Dry and Wet Events P. Spennemann et al. https://doi.org/10.1175/JHM-D-17-0015.1
3794. Transport-based transfer learning on Electronic Health Records: application to detection of treatment disparities W. Li et al. https://doi.org/10.1093/jamia/ocaf134
3795. Determining building-specific wind pressure coefficients to account for the microclimate in the calculation of air infiltration in buildings S. Charisi et al. https://doi.org/10.1080/17512549.2019.1596835
3796. Prediction of offshore wind turbine wake and output power using large eddy simulation and convolutional neural network S. LIU et al. https://doi.org/10.1016/j.enconman.2024.119326
3797. A feature weighted support vector machine and artificial neural network algorithm for academic course performance prediction C. Huang et al. https://doi.org/10.1007/s00521-021-05962-3
3798. A State-by-State online transfer learning framework with incremental clustering for blood glucose prediction X. Zhang et al. https://doi.org/10.1016/j.bspc.2023.105200
3799. A new proportionality-based back-calculation approach, which employs traditional forms of growth equations, improves estimates of length at age E. Ashworth et al. https://doi.org/10.1139/cjfas-2016-0409
3800. Enhanced Sea Surface Salinity Estimates Using Machine-Learning Algorithm With SMAP and High-Resolution Buoy Data B. Kesavakumar et al. https://doi.org/10.1109/ACCESS.2022.3189784
3801. 3-D Computed Laminography Based on a Sequential Regularization Y. Liu et al. https://doi.org/10.1109/TNS.2025.3574888
3802. MDLdroidLite: A Release-and-Inhibit Control Approach to Resource-Efficient Deep Neural Networks on Mobile Devices Y. Zhang et al. https://doi.org/10.1109/TMC.2021.3062575
3803. Machine learning for compositional disorder: A comparison between different descriptors and machine learning frameworks M. Yaghoobi & M. Alaei https://doi.org/10.1016/j.commatsci.2022.111284
3804. Frequency Seismic Response for EEWS Testing on Uniaxial Shaking Table C. Donciu et al. https://doi.org/10.3390/e25040655
3805. Assessment of data intelligence algorithms in modeling daily reference evapotranspiration under input data limitation scenarios in semi-arid climatic condition J. Rajput et al. https://doi.org/10.2166/wst.2023.137
3806. Data-efficient creativity evaluation in museum cultural creative products: a machine learning framework for data-driven decision-making in product development H. Cheng et al. https://doi.org/10.1016/j.eswa.2025.129014
3807. Spatial modelling of accidents risk caused by driver drowsiness with data mining algorithms F. Farhangi et al. https://doi.org/10.1080/10106049.2020.1831626
3808. Metal Eklemeli ve Geleneksel İmalat Yöntemleriyle Üretilen Alüminyum Profillerin Sıcaklık Davranışının Bulanık Mantık ve Yapay Zekâ Tabanlı Modellemesi K. Özsoy & B. Aksoy https://doi.org/10.35234/fumbd.1739022
3809. Forest Fuel Load Estimation Using Combined Sentinel-1 and Sentinel-2 Data: A Case Study of the Greater Khingan Mountains in China P. Zhou et al. https://doi.org/10.1109/ACCESS.2025.3542128
3810. Unsupervised Abnormal Sensor Signal Detection With Channelwise Reconstruction Errors M. Kwak & S. Kim https://doi.org/10.1109/ACCESS.2021.3064563
3811. A framework for modeling and testing forecasting in agricultural production systems S. Chadli et al. https://doi.org/10.1007/s41207-025-00876-1
3812. A comparative analysis of the ecological impacts of Chinese tuna longline fishery on the Eastern Pacific Ocean Q. Lin et al. https://doi.org/10.1016/j.ecolind.2022.109284
3813. SSGCL: Simple Social Recommendation with Graph Contrastive Learning Z. Duan et al. https://doi.org/10.3390/math12071107
3814. Quantification of natural rubber blends by reflection/reflectance infrared and confocal Raman spectroscopy: a comparison of statistical methods A. PASSERO et al. https://doi.org/10.1590/0001-3765202420230387
3815. Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms S. Tian et al. https://doi.org/10.1007/s11356-022-23431-9
3816. Fault Diagnosis of Wind Turbine Generators Based on Stacking Integration Algorithm and Adaptive Threshold Z. Tang et al. https://doi.org/10.3390/s23136198
3817. Improving Forest Canopy Cover Mapping Through ICESat-2-Derived Understory DEM and Multisource Remote Sensing Data M. Wang et al. https://doi.org/10.1109/JSTARS.2026.3729194
3818. Sequence-Aware Deep Learning for Field-Scale Surface Soil Moisture Estimation from Sentinel-1, HLS, and Ancillary Data E. Jahan Nejadi et al. https://doi.org/10.3390/rs18132213
3819. Classification Performance Improvement Using Random Subset Feature Selection Algorithm for Data Mining L. D & B. Vishnuvardhan https://doi.org/10.1016/j.bdr.2018.02.007
3820. A review of time series forecasting and spatio-temporal series forecasting in deep learning Q. Yu et al. https://doi.org/10.1007/s11227-025-07632-w
3821. Toward Enhanced State of Charge Estimation of Lithium-ion Batteries Using Optimized Machine Learning Techniques M. Hannan et al. https://doi.org/10.1038/s41598-020-61464-7
3822. Assessment of Salinization Through ANN Learned with Remote Sensing and DEM Data in Soils of the Lower Cheliff Plain (Algeria) A. Ziane et al. https://doi.org/10.1007/s12524-022-01552-5
3823. Analysis of Precipitation Totals Based on Radar and Rain Gauge Data K. Dzwonkowski et al. https://doi.org/10.3390/rs17132157
3824. Accurate prediction of kiwifruit soluble solids content using an optimized 1D-CNN model with near-infrared spectroscopy W. Geng et al. https://doi.org/10.1080/10942912.2025.2581384
3825. Evaluation of multiple linear regression function and generalized linear model types in estimating natural menopausal age: A crosssectional study N. Sadeghi et al. https://doi.org/10.18502/ijrm.v20i5.11052
3826. Analysis of the Likelihood Function and Cutoff Threshold in the GLUE Procedure for Calibration of the Resistance Parameters of Mountain Rivers S. Cedillo et al. https://doi.org/10.1007/s11269-024-03869-x
3827. Building a Lucy hybrid model for grocery sales forecasting based on time series D. Tran et al. https://doi.org/10.1007/s11227-022-04824-6
3828. Improving the Accuracy of Water Storage Anomaly Trends Based on a New Statistical Correction Hydrological Model Weighting Method Q. Wang et al. https://doi.org/10.3390/rs13183583
3829. Integration of WRF-Chem Model-Based, Satellite-Based, and Ground-Based Observation Data to Predict PM2.5 Concentration by Machine Learning Approach S. Chimla et al. https://doi.org/10.3390/atmos16111304
3830. Root mean square error or mean absolute error? Use their ratio as well D. Karunasingha https://doi.org/10.1016/j.ins.2021.11.036
3831. Product Design Incorporating Competition Relations: A Network-Based Design Framework Considering Local Dependencies Y. Xiao et al. https://doi.org/10.1115/1.4066426
3832. Investigating statistical bias correction with temporal subsample of the upper Ping River Basin, Thailand S. Wuthiwongtyohtin https://doi.org/10.2166/wcc.2020.021
3833. Bessel-beam-assisted persistent current in toroidal semiconductor quantum dots S. Gavalajyan et al. https://doi.org/10.1016/j.mtcomm.2026.114781
3834. High-precision shape reconstruction for optical fiber sensors based on cubic spline interpolation and tangent angle recursion Y. Liu & H. Ji https://doi.org/10.3389/fphy.2025.1665822
3835. Estimation of missing hydrological data in monthly rainfall series using meteorological satellite data E. dos Santos et al. https://doi.org/10.1007/s12665-021-09409-9
3836. Expressway Exit Traffic Flow Prediction for ETC and MTC Charging System Based on Entry Traffic Flows and LSTM Model Z. Chen et al. https://doi.org/10.1109/ACCESS.2021.3070625
3837. Groundwater level forecasting in a data-scarce region through remote sensing data downscaling, hydrological modeling, and machine learning: A case study from Morocco A. Rafik et al. https://doi.org/10.1016/j.ejrh.2023.101569
3838. Hierarchical Bayesian model for joint prediction of runway pavement metrics considering measurement uncertainty A. Altarabsheh et al. https://doi.org/10.1139/cjce-2025-0075
3839. From short to long-term horizons: Comparative assessment of Machine Learning and Deep Learning for river stage prediction with spatial transferability analysis M. Islam et al. https://doi.org/10.1016/j.rineng.2025.108194
3840. Multi-sensor phenotyping of yield and yield stability for genotype selection in durum wheat J. Jauregui-Besó et al. https://doi.org/10.1016/j.plaphe.2026.100178
3841. Predicting seakeeping of conventional monohull vessels with forward speed using artificial neural networks P. Romero-Tello et al. https://doi.org/10.1007/s40722-025-00395-9
3842. Harnessing machine learning models and explainable AI to understand MOOC continuance intention V. Sharma et al. https://doi.org/10.1108/IDD-09-2024-0133
3843. Prediction of multi-year winter wheat yields at the field level with satellite and climatological data M. Marszalek et al. https://doi.org/10.1016/j.compag.2022.106777
3844. Validation of LAI, chlorophyll and FVC biophysical estimates from sentinel-2 level 2 prototype processor over a heterogeneous savanna and grassland environment in South Africa P. Tsele et al. https://doi.org/10.1080/10106049.2022.2087756
3845. Study of Learning Techniques for Effort Estimation in Object-Oriented Software Development S. Shukla & S. Kumar https://doi.org/10.1109/TEM.2022.3217570
3846. Assessing drug consumption patterns in Canadian cities through wastewater analysis D. McCulloch et al. https://doi.org/10.1186/s12982-026-01494-0
3847. An Auto-Extraction Framework for CEP Rules Based on the Two-Layer LSTM Attention Mechanism: A Case Study on City Air Pollution Forecasting Y. Liu et al. https://doi.org/10.3390/en15165892
3848. High-energy neutron shielding analysis using curve fitting and machine learning: a Monte Carlo-based study in concrete and Ferro-Boron configurations A. Gökcan & D. Sarıyer https://doi.org/10.1016/j.anucene.2026.112244
3849. Research on the Development and Application of a Deep Learning Model for Effective Management and Response to Harmful Algal Blooms J. Kim et al. https://doi.org/10.3390/w15122293
3850. Deciphering the character of public transport participation in subjective well-being: Evidence from Hangzhou, China Y. Dong et al. https://doi.org/10.1016/j.jth.2024.101923
3851. Energy Consumption Prediction of Injection Molding Process Based on Rolling Learning Informer Model J. Huang et al. https://doi.org/10.3390/polym16213097
3852. WRF‐based dynamical downscaling of ERA5 reanalysis data for High Mountain Asia: Towards a new version of the High Asia Refined analysis X. Wang et al. https://doi.org/10.1002/joc.6686
3853. Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity T. Pham et al. https://doi.org/10.1371/journal.pone.0243030
3854. Machine learning framework for forecasting air pollution: Evaluating seasonal and climatic influences in Istanbul, Turkey N. AL-Rousan et al. https://doi.org/10.1371/journal.pone.0330716
3855. Predictive model for growth of Clostridium botulinum from spores during cooling of cooked ground chicken V. Juneja et al. https://doi.org/10.1016/j.foodres.2021.110695
3856. Optimizing thermal comfort in highly automated vehicles: An AI-Based HVAC management approach with radiant panels for winter conditions M. Kipp et al. https://doi.org/10.1016/j.enbuild.2026.117113
3857. A robust approach to shear strength prediction of reinforced concrete deep beams using ensemble learning with SHAP interpretability A. Tiwari et al. https://doi.org/10.1007/s00500-023-09495-w
3858. SRDiff: Single image super-resolution with diffusion probabilistic models H. Li et al. https://doi.org/10.1016/j.neucom.2022.01.029
3859. Hydrological drought risk recurrence under climate change in the karst area of Northwestern Algeria S. Bouabdelli et al. https://doi.org/10.2166/wcc.2020.207
3860. Saturation Flow Rate at the Work Zone–Straddled Intersections with Interweaving Movements: Lane-Based Modeling Study Z. Yan et al. https://doi.org/10.1061/JTEPBS.0000718
3861. XAI-Supported Multi-Algorithm Budget Forecasting Model: Analysis of Türkiye’s Fiscal Sustainability and Parameter Importances for the Period 1999–2024 E. Yılmaz İnce et al. https://doi.org/10.30798/makuiibf.1764796
3862. Characteristics and simplified model of film slit irrigation Y. Li et al. https://doi.org/10.1080/03650340.2018.1477254
3863. Random-forest based adjusting method for wind forecast of WRF model A. Wang et al. https://doi.org/10.1016/j.cageo.2021.104842
3864. Error Correction Based Deep Neural Networks for Modeling and Predicting South African Wildlife–Vehicle Collision Data I. Nandutu et al. https://doi.org/10.3390/math10213988
3865. New method for damage detection in steel beam using time-frequency functions and machine learning H. Hooshyar et al. https://doi.org/10.1016/j.istruc.2025.109236
3866. QSPR estimation models of normal boiling point and relative liquid density of pure hydrocarbons using MLR and MLP-ANN methods M. Roubehie Fissa et al. https://doi.org/10.1016/j.jmgm.2018.11.013
3867. Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective N. Mehdiyev et al. https://doi.org/10.1007/s10479-024-05943-4
3868. Ag/TiO2-functionalized photocatalytic concrete for visible-light photocatalytic degradation of reactive black 5: Experimental optimization, mechanistic insights and machine learning modeling N. Nfor et al. https://doi.org/10.1016/j.jsamd.2026.101170
3869. Benchtop validation of a low-cost wearable triaxial accelerometer C. Silva et al. https://doi.org/10.1088/2057-1976/ae866e
3870. Accuracy of Thoracic Tape-Based Live-Weight Estimation in Minhota Calves: Effects of Age, Sex and Dam Parity F. Mata et al. https://doi.org/10.3390/ruminants6030065
3871. A stochastic differential equation approach to the analysis of the UK 2016 EU referendum polls T. Fenner et al. https://doi.org/10.1088/2399-6528/aac347
3872. Prediction of Probability of Liquefaction Using Soft Computing Techniques D. Kumar et al. https://doi.org/10.1007/s40030-022-00683-9
3873. Data-driven prediction of electrospun nanofiber diameter using machine learning: A comprehensive study and web-based tool development S. Sukpancharoen et al. https://doi.org/10.1016/j.rineng.2024.102826
3874. Estimating NOx LOTOS-EUROS CTM Emission Parameters over the Northwest of South America through 4DEnVar TROPOMI NO2 Assimilation A. Yarce Botero et al. https://doi.org/10.3390/atmos12121633
3875. Can Quantized On-Premise LLMs Flag Semantic Inflation in Employee Work Logs? A Privacy-Preserving Decision-Support Workflow S. Gao & M. Huang https://doi.org/10.1109/ACCESS.2026.3702481
3876. Determination of full maturity in soybean using machine-learning models and UAV imagery P. Arantes et al. https://doi.org/10.1590/1984-70332026v26n3a36
3877. Robust AI-based Cobb angle measurement using dual-source X-ray radiographic datasets and pretrained CNNs L. Fraiwan & H. AbuKhalaf https://doi.org/10.1007/s10586-026-05991-4
3878. Mathematical vector framework for gravity-specific land surface curvatures calculation from triangulated irregular networks G. Hu et al. https://doi.org/10.1080/15481603.2022.2044149
3879. The efficacy of deep learning based LSTM model in forecasting the outbreak of contagious diseases N. Absar et al. https://doi.org/10.1016/j.idm.2021.12.005
3880. Accurate pollutant removal performance prediction of constructed wetlands using multi-source time-series data and interpretable machine learning J. Wang et al. https://doi.org/10.1016/j.jclepro.2026.148501
3881. Predicting Livestock Farmers’ Attitudes towards Improved Sheep Breeds in Ahar City through Data Mining Methods J. Vahedi et al. https://doi.org/10.3390/world5040044
3882. Climate Change and Respiratory Diseases: Relationship between SARS and Climatic Parameters and Impact of Climate Change on the Geographical Distribution of SARS in Iran G. Bahrami et al. https://doi.org/10.3390/arm90050048
3883. Predicting biochar adsorption capacity for methylene blue removal using machine learning P. Rajput et al. https://doi.org/10.1016/j.jwpe.2024.106749
3884. Comparison of TLS and SLAM technologies for 3D reconstruction of objects with different geometries A. Szrek et al. https://doi.org/10.1088/1755-1315/1295/1/012012
3885. Generalized ANN Model for Predicting the Energy Potential of Heterogeneous Waste I. Brandić et al. https://doi.org/10.3390/en18236111
3886. PERMACLIM 2.0: a Revised Model for High-Resolution Mapping of Permafrost Conditions in Mountain Regions E. Riva et al. https://doi.org/10.1007/s41651-026-00269-0
3887. Effects of the Training Data Condition on Arterial Spin Labeling Parameter Estimation Using a Simulation-Based Supervised Deep Neural Network S. Ishida et al. https://doi.org/10.1097/RCT.0000000000001566
3888. Performance-based durability assessment of nano-enhanced alccofine mortar under H2SO4 and MgSO4 exposure: response-surface analysis and kinetic modeling V. Wadki & B. B https://doi.org/10.1007/s41024-026-00866-y
3889. Collaborative evaluation of in silico predictions for high throughput toxicokinetics J. Wambaugh et al. https://doi.org/10.1016/j.tiv.2025.106150
3890. Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach R. Prasad et al. https://doi.org/10.1016/j.catena.2019.02.012
3891. 大直径回转体零部件壳体局部加速器CT检测 詹. Zhan Meina et al. https://doi.org/10.3788/AOS241179
3892. Prediction of blast-induced ground vibration in dolomitic marble quarry using Z-number information and fuzzy cognitive map based neural network models S. Hosseini et al. https://doi.org/10.1016/j.rockmb.2025.100217
3893. Modèle tabulaire adaptatif de classement des outils intelligents d’aide à la conception architecturale L. Roobaert et al. https://doi.org/10.1051/shsconf/202419802003
3894. Earth fissure susceptibility mapping: Application of random subspace‐based novel ensemble approaches M. Santosh et al. https://doi.org/10.1002/gj.4932
3895. Review-Based Recommender System Using Outer Product on CNN S. Hong et al. https://doi.org/10.1109/ACCESS.2024.3393417
3896. Potential of Mobile LiDAR Sensors in Hiking Trail Management R. Fernandes et al. https://doi.org/10.3390/s26165143
3897. Detecting and Tracking the Positions of Wild Ungulates Using Sound Recordings S. Salem et al. https://doi.org/10.3390/s21030866
3898. Comparative metaheuristic optimization of a multilayer SPR sensor for arsenic monitoring in groundwater in Bangladesh K. Imam et al. https://doi.org/10.1016/j.rio.2026.101134
3899. Predictive modelling of tugboat propulsion loads using machine learning: a case study on Istanbul Strait maritime operation O. Yuksel et al. https://doi.org/10.1080/17445302.2026.2672462
3900. Skill of short- to medium-range monsoon rainfall forecasts from two global models over India for hydro-meteorological applications S. Prakash et al. https://doi.org/10.1002/met.1579
3901. Geostatistical based framework for spatial modeling of groundwater level during dry and wet seasons in an arid region: a case study at Hadat Ash-Sham experimental station, Saudi Arabia J. Budiman et al. https://doi.org/10.1007/s00477-021-01971-9
3902. Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data Limitations C. Brzakala et al. https://doi.org/10.1021/acs.jcim.5c03121
3903. Kinetic Modeling of Anaerobic Co-Digestion Of Plant Solid Waste with Sewage Sludge: Synergistic Influences of Total Solids and Substrate Particle Size in Biogas Generation V. Leite et al. https://doi.org/10.1007/s12155-023-10677-5
3904. Y90 Radyoembolizasyon Tedavisinde Makine Öğrenmesi ile Aktivite Tahmini H. TANYILDIZI KÖKKÜLÜNK et al. https://doi.org/10.35234/fumbd.1162466
3905. XGBoost regression for robust acoustic impedance prediction in the absence of density and sonic logs K. Saleh et al. https://doi.org/10.1038/s41598-025-24727-9
3906. Multitemporal impervious surface estimation via an optimized stable/change pixel detection approach W. Fan et al. https://doi.org/10.1080/15481603.2022.2118430
3907. Adoption of Digital Aerial Photogrammetry in Forest Planning: A Case Study of Canavese Forestry Consortium, NW Italy with Technical and Economic Issues E. Borgogno-Mondino et al. https://doi.org/10.3390/land11081350
3908. Effective Training Data Extraction Method to Improve Influenza Outbreak Prediction from Online News Articles: Deep Learning Model Study B. Jang et al. https://doi.org/10.2196/23305
3909. Comparative Evaluation of Remote Sensing Platforms for Almond Yield Prediction N. Guimarães et al. https://doi.org/10.3390/agriengineering6010015
3910. A Chlorophyll Concentration Inversion Method Based on OWTs and 1D CNN-Transformer Feature Extraction Y. Cui et al. https://doi.org/10.1109/JSTARS.2025.3641630
3911. Thermal Data Optimization Through Uncertainty Reduction in Fatigue Limits Estimation: A TCM–ANN Framework for C45 Steel L. Corsaro et al. https://doi.org/10.3390/met16010042
3912. Visual analysis of inscriptions in the Tang Dynasty: a case study on the calligraphy style of Wang Xizhi Y. Zhang et al. https://doi.org/10.1007/s44267-023-00012-z
3913. A dataset of NDVI predictions for the Qinghai-Tibet Plateau based on CMIP6 (2025&ndash;2100) Z. ZHANG et al. https://doi.org/10.11922/11-6035.csd.2025.0093.zh
3914. Predictive model for the spreadability of cosmetic formulations based on large amplitude oscillatory shear (LAOS) and machine learning S. Lee et al. https://doi.org/10.1063/5.0117989
3915. Machine learning analysis of socioeconomic drivers in urban ozone pollution in Chinese cities K. Xiang et al. https://doi.org/10.1007/s10661-024-12489-2
3916. Field performance assessment and calibration of multi-depth AquaCheck capacitance-based soil moisture probes under permanent pasture for hill country soils I. Hajdu et al. https://doi.org/10.1016/j.agwat.2019.03.002
3917. Critical statistical assessment of data in metal additive manufacturing R. Wong et al. https://doi.org/10.1016/j.matdes.2025.114301
3918. RVDCU-Net: A Modular Deep Learning Framework for Spatiotemporal Reconstruction of Satellite-Derived Sea Surface Temperature T. Qi et al. https://doi.org/10.1080/01490419.2025.2583086
3919. From local data to global risk maps: A geospatial generative pre-trained transformer framework for earthquake building vulnerability estimation S. Pirasteh et al. https://doi.org/10.1016/j.gsf.2026.102445
3920. Simulation and Assimilation of CO2 Concentrations Based on the WRF-Chem Model W. Liu et al. https://doi.org/10.3390/pr13124010
3921. Laser Cladding of Stellite-6 on AISI 316 L Austenitic Stainless Steel: Empirical-Statistical Modeling and Parameter Optimization J. Pacheco et al. https://doi.org/10.1007/s40516-020-00132-0
3922. Improving the generalization error and transparency of regression models to estimate soil organic carbon using soil reflectance data E. dos Santos et al. https://doi.org/10.1016/j.ecoinf.2023.102240
3923. Weather-Aware Prediction of Trail Running Finish Times Using Machine Learning M. Darunnaja et al. https://doi.org/10.59395/ijadis.v7i2.1610
3924. Digital Forensics AI: Evaluating, Standardizing and Optimizing Digital Evidence Mining Techniques A. Solanke & M. Biasiotti https://doi.org/10.1007/s13218-022-00763-9
3925. Comparison of two fine scale spatial models for mapping temperatures inside winegrowing areas R. Le Roux et al. https://doi.org/10.1016/j.agrformet.2017.07.020
3926. Analysis of the accuracy of in-situ concrete characteristic compressive strength assessment in real structures using destructive and non-destructive testing methods K. Ali-Benyahia et al. https://doi.org/10.1016/j.conbuildmat.2022.130161
3927. Deciphering cell–cell communication at single-cell resolution for spatial transcriptomics with subgraph-based graph attention network W. Yang et al. https://doi.org/10.1038/s41467-024-51329-2
3928. The Impact of Cost Items on the Development Cost of Shopping Centers B. Şahin Diri https://doi.org/10.3390/buildings16193908
3929. A substructure method with coupled explicit-implicit strategy for long-span wave-bridge FSI analysis X. Yin et al. https://doi.org/10.1016/j.oceaneng.2026.126751
3930. Validation of the Overseer Cropping Model for Estimating Nitrate Leaching Losses in Precision Agriculture R. Bawatharani et al. https://doi.org/10.3390/nitrogen7010017
3931. Novel soft computing hybrid model for predicting shear strength and failure mode of SFRC beams with superior accuracy W. Chaabene & M. Nehdi https://doi.org/10.1016/j.jcomc.2020.100070
3932. A comparison of Support Vector Machines and Bayesian algorithms for landslide susceptibility modelling B. Pham et al. https://doi.org/10.1080/10106049.2018.1489422
3933. RadarDiff: A Conditional Diffusion Model With Time-Aware Context and Mixed Attention for Radar Echo Extrapolation H. Geng et al. https://doi.org/10.1109/JSTARS.2026.3722210
3934. Analyzing and Forecasting Admission data using Time Series Model N. Muhamad & H. Thamrin https://doi.org/10.15575/join.v5i1.546
3935. Application of HEC-HMS Model for Evaluation of Rainwater Harvesting Potential in a Semi-arid City A. Ndeketeya & M. Dundu https://doi.org/10.1007/s11269-021-02941-0
3936. Gated-LNN: Gated Liquid Neural Networks for Accurate Water Quality Index Prediction and Classification S. Chadalavada et al. https://doi.org/10.1109/ACCESS.2025.3561593
3937. CoRoPINN: Cognitive region optimized physics-informed neural networks J. Li et al. https://doi.org/10.1371/journal.pone.0358646
3938. An Attentive Aspect-Based Recommendation Model With Deep Neural Network S. Yang et al. https://doi.org/10.1109/ACCESS.2023.3349291
3939. Urban air temperature model using GOES-16 LST and a diurnal regressive neural network algorithm J. Hrisko et al. https://doi.org/10.1016/j.rse.2019.111495
3940. Multi-objective robust optimization for enhanced safety in large-diameter tunnel construction with interactive and explainable AI P. Lin et al. https://doi.org/10.1016/j.ress.2023.109172
3941. Smart solutions for maize farmers: Machine learning-enabled web applications for downy mildew management and enhanced crop yield in India J. G et al. https://doi.org/10.1016/j.eja.2024.127441
3942. Neural Network-Assisted Modeling and High-Temperature Degradation Analysis of SOI NMOSFET Electrical Characteristics T. Deng et al. https://doi.org/10.1016/j.mejo.2026.107531
3943. Robust State‐of‐Charge Estimation for Lithium‐Ion Batteries Using an Adaptive Invariant Extended Kalman Filter With an Enhanced Self‐Correcting Model M. Thekkedath & S. Dash https://doi.org/10.1002/est2.70545
3944. Inulinase production and mathematical modeling from carob extract by using Aspergillus niger M. Ilgın et al. https://doi.org/10.1002/btpr.2919
3945. Determination of Libidibia ferrea Markers Using Spectrophotometry and Chemometric Tools with Comparison to a Standard High-Performance Liquid Chromatography (HPLC) Protocol M. Andrade et al. https://doi.org/10.1080/00032719.2022.2032123
3946. A Peak Traffic Congestion Prediction Method Based on Bus Driving Time Z. Huang et al. https://doi.org/10.3390/e21070709
3947. Influence of large scale climate drivers on hydro-climate variability in Dwangwa River Basin, Malawi A. Chirwa et al. https://doi.org/10.1007/s44292-024-00007-5
3948. Prediction of Digestible and Metabolizable Energy in Swine Feed Using Machine Learning J. Yu et al. https://doi.org/10.1021/acsomega.6c03545
3949. Evaluation of complete-arch implant scanning with 5 different intraoral scanners in terms of trueness and operator experience G. Revell et al. https://doi.org/10.1016/j.prosdent.2021.01.013
3950. Potential field data interpretation to detect the parameters of buried geometries by applying a nonlinear least-squares approach K. Essa & E. Abo-Ezz https://doi.org/10.1007/s40328-021-00337-5
3951. Artificial Neural Networks in Corrosion Prediction and Modeling: A Critical Review of Advances, Limitations, and Future Prospects C. Njoku et al. https://doi.org/10.1007/s40735-026-01218-6
3952. Variations of B0 and B1 with the solar quiet Sq-current system and comparison with IRI-2012 model at Ilorin S. Bello et al. https://doi.org/10.1016/j.asr.2017.02.003
3953. Thermal-hydraulic performance and design screening of a Y-shaped bifurcated honeycomb microchannel heat sink S. Ding et al. https://doi.org/10.1016/j.icheatmasstransfer.2026.111694
3954. Forecasting Energy Consumption of a Public Building Using Transformer and Support Vector Regression J. Huang & S. Kaewunruen https://doi.org/10.3390/en16020966
3955. Assessing Rodent-Induced Ecological Disturbance in Natural Grasslands Using Multi-Source Spatial Data M. Huang et al. https://doi.org/10.3390/ani16142260
3956. Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models H. Ly et al. https://doi.org/10.1007/s00521-020-05214-w
3957. NASGP: An efficient and interpretable neural architecture search framework for plant genomic prediction Y. Rao et al. https://doi.org/10.1016/j.indcrop.2026.124009
3958. How important is to detect systematic error in predictions and understand statistical applicability domain of QSAR models? K. Roy et al. https://doi.org/10.1016/j.chemolab.2017.01.010
3959. Hydropower projects investment estimation artificial intelligence model by similarity measure-based few-shot machine learning M. Shi et al. https://doi.org/10.1016/j.engappai.2025.110891
3960. Predicting aggregate stability index in ferralsols T. de Melo et al. https://doi.org/10.1111/sum.12453
3961. Integrated RSM and machine learning approach for surface topography optimization in SLA 3D-printed functional components E. Yıldız & M. Albaşkara https://doi.org/10.1088/2051-672X/ae4118
3962. Prediction of evaporation in arid and semi-arid regions: a comparative study using different machine learning models Z. Yaseen et al. https://doi.org/10.1080/19942060.2019.1680576
3963. CORAL: Development of a hybrid descriptor based QSTR model to predict the toxicity of dioxins and dioxin-like compounds with correlation intensity index and consensus modelling P. Kumar et al. https://doi.org/10.1016/j.etap.2022.103893
3964. Evaluation of precipitation datasets over Greece. Insights from comparing multiple gridded products with observations K. Papa & A. Koutroulis https://doi.org/10.1016/j.atmosres.2024.107888
3965. Research on the Prediction of Higher Heating Value of Biochar Based on Machine Learning Trained with “Enhanced Data” C. Zhao et al. https://doi.org/10.1007/s12155-025-10895-z
3966. Tunneling-induced settlement prediction using the hybrid feature selection method for feature optimization Y. Cheng et al. https://doi.org/10.1016/j.trgeo.2022.100808
3967. Evaluation metrics in medical imaging AI: fundamentals, pitfalls, misapplications, and recommendations B. Kocak et al. https://doi.org/10.1016/j.ejrai.2025.100030
3968. Machine learning based technique for characterization of magnetocaloric entropy performance: a study on formula (La0.67Ca(0.33-x)SrₓMn0.98Ni0.02O3)1-y/(La0.67Ca0.33MnO3)y manganite composites K. Laajimi et al. https://doi.org/10.1007/s42247-026-01345-3
3969. Effective and efficient incomplete multivariate time series forecasting H. Shi et al. https://doi.org/10.1016/j.eswa.2026.132412
3970. A construction method of a multidimensional and multilingual association network for earth surface system science data Q. Qiu et al. https://doi.org/10.1080/17538947.2025.2522388
3971. Assessing the Applicability of the LTSF Algorithm for Streamflow Time Series Prediction: Case Studies of Dam Basins in South Korea J. Park et al. https://doi.org/10.3390/w17223214
3972. A multi-fidelity approach for predicting the mechanical properties of composite triply periodic minimal surface structures T. Mair et al. https://doi.org/10.1016/j.jmrt.2026.09.125
3973. Ensemble learning models to predict the compressive strength of geopolymer concrete: a comparative study for geopolymer composition design Q. Tian et al. https://doi.org/10.1007/s41939-023-00303-4
3974. Rapid monitoring of heavy metal-ammonia complexes in solutions by UV–vis/ATR-FTIR spectroscopy and chemometric models Z. Liu et al. https://doi.org/10.1016/j.cej.2024.148692
3975. Machine learning-based prediction of species mass fraction and flame characteristics in partially premixed turbulent jet flame A. Shateri et al. https://doi.org/10.1063/5.0277024
3976. Digital biomarkers for interstitial glucose prediction in healthy individuals using wearables and machine learning X. Huang et al. https://doi.org/10.1038/s41598-025-14172-z
3977. Hourly PM2.5 Forecasting for Sustainable Urban Air Quality Management Through Multiresolution Learning and Environmental Context S. Cheng et al. https://doi.org/10.3390/su182010531
3978. From iteration to instantaneity: a new deep learning approach for inverse design of indoor environment J. Li et al. https://doi.org/10.1080/23744731.2026.2665560
3979. Framework for predicting multi-sector business interruption losses solely from earthquake scenarios Q. Mao et al. https://doi.org/10.1016/j.ijdrr.2026.106034
3980. Accuracy of Automatic Passenger Counting in Open Mass Transit Systems: Insights from Italy B. Barabino et al. https://doi.org/10.2174/0126671212383074250407062430
3981. Evaluation of ionospheric models for Central and South Americas T. Klipp et al. https://doi.org/10.1016/j.asr.2019.09.005
3982. Projection of future extreme precipitation in Iran based on CMIP6 multi-model ensemble A. Zarrin & A. Dadashi-Roudbari https://doi.org/10.1007/s00704-021-03568-2
3983. Accurate VLE Predictions via COSMO-RS-Guided Deep Learning Models: Solubility and Selectivity in Physical Solvent Systems for Carbon Capture E. Parascandolo et al. https://doi.org/10.1021/acs.jcim.5c01148
3984. SolarET: A generalizable machine learning approach to estimate reference evapotranspiration from solar radiation A. Ahmadi et al. https://doi.org/10.1016/j.agwat.2024.108779
3985. Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping S. Razavi-Termeh et al. https://doi.org/10.1016/j.ecoinf.2025.103326
3986. Machine learning-enabled nanosafety assessment of multi-metallic alloy nanoparticles modified TiO2 system P. Regonia et al. https://doi.org/10.1016/j.impact.2022.100442
3987. Concrete corrosion in wastewater systems: Prediction and sensitivity analysis using advanced extreme learning machine M. Zounemat-Kermani et al. https://doi.org/10.1007/s11709-021-0697-9
3988. Travel distance estimation of landslide-induced debris flows by machine learning method in Nepal Himalaya after the Gorkha earthquake C. Qiu & X. Geng https://doi.org/10.1007/s10064-024-03883-8
3989. Implementation of flexible models to bioethanol production from carob extract–based media in a biofilm reactor M. Germec et al. https://doi.org/10.1007/s13399-020-00612-5
3990. Machine-Learning Modeling of Asphalt Crack Treatment Effectiveness Z. Huang et al. https://doi.org/10.1061/JPEODX.0000274
3991. Statistical analysis of modified Hargreaves equation for precise estimation of reference evapotranspiration R. Habeeb et al. https://doi.org/10.1080/16000870.2021.1966869
3992. Time-series data optimized AR/ARMA model for frugal spectrum estimation in Cognitive Radio D. Chakraborty & S. Sanyal https://doi.org/10.1016/j.phycom.2020.101252
3993. Improving GNSS-IR Sea Surface Height Accuracy Based on a New Ionospheric Stratified Elevation Angle Correction Model J. Zhu et al. https://doi.org/10.3390/rs16173270
3994. MACHINE LEARNING AND VALIDATION STRATEGIES IN PANEL DATA-BASED GREENHOUSE GAS EMISSION MODELING D. Demircioğlu Diren https://doi.org/10.18038/estubtda.1891746
3995. Pancreatic fibrosis assessment and association with pancreatic cancer: comparison with the extracellular volume fraction H. Fukui et al. https://doi.org/10.1016/j.crad.2024.08.007
3996. Histogram tabanlı gradyan artırma yöntemi ile Türkiye için kısa vadeli elektrik talep tahmini H. Karamollaoğlu https://doi.org/10.28948/ngumuh.1817112
3997. TRIAGE: Trustworthy Reporting and Assessment for Clinical Gain and Effectiveness of AI Models F. Fazilati et al. https://doi.org/10.3390/diagnostics16050666
3998. AI-powered hotel performance prediction: a multimodal data approach N. Li et al. https://doi.org/10.1108/IJCHM-11-2025-1744
3999. Rapid construction of safe-zone by active flow field control and sparse-sampling-perception-network for public indoor environments suffering from nerve agents X. Gao et al. https://doi.org/10.1016/j.buildenv.2022.109961
4000. Compressed neural networks for reduced order modeling Y. Zhu et al. https://doi.org/10.1063/5.0194598
4001. Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peel Y. Wong et al. https://doi.org/10.1007/s10661-020-08268-4
4002. Using Pythagorean Expectation to Determine Luck in the KFC Big Bash League A. Vine https://doi.org/10.1111/1759-3441.12139
4003. Multiple hypothesis testing in cognitive IoT sensor network V. Jha & P. Tripathi https://doi.org/10.1016/j.adhoc.2024.103559
4004. Novel GA-Based DNN Architecture for Identifying the Failure Mode with High Accuracy and Analyzing Its Effects on the System N. Rezaeian et al. https://doi.org/10.3390/app14083354
4005. Dynamic resource provisioning for service-based cloud applications: A Bayesian learning approach R. Panwar & M. Supriya https://doi.org/10.1016/j.jpdc.2022.06.001
4006. A protein fitness predictive framework based on feature combination and intelligent searching Z. Zhang et al. https://doi.org/10.1002/pro.5211
4007. The potential of hyperspectral images and partial least square regression for predicting total carbon, total nitrogen and their isotope composition in forest litterfall samples I. Tahmasbian et al. https://doi.org/10.1007/s11368-017-1751-z
4008. Fault Classification and Precise Fault Location Detection in 400 kV High-Voltage Power Transmission Lines Using Machine Learning Algorithms Ö. Özdemir et al. https://doi.org/10.3390/pr13020527
4009. Estimating evapotranspiration in semi-arid rangelands: connecting reference to actual evapotranspiration and the role of soil evaporation O. Gwate et al. https://doi.org/10.2989/10220119.2018.1505779
4010. A general finite deformation hypoelastic-plasticity non-ordinary state-based peridynamics model and its applications R. Liu et al. https://doi.org/10.1007/s00366-023-01792-0
4011. Temperature prediction of combustion level of ultra-supercritical unit through data mining and modelling X. Li et al. https://doi.org/10.1016/j.energy.2021.120875
4012. Surface ozone trend variability across the United States and the impact of heat waves (1990–2023) K. Chang et al. https://doi.org/10.5194/acp-25-5101-2025
4013. Estimating large birds’ radar cross-section for aeroecology studies using T-matrix modelling K. Reznikov et al. https://doi.org/10.1098/rsif.2025.0510
4014. Machine learning insights into catalyst composition and structural effects on CH4 selectivity in iron-based fischer tropsch synthesis Y. Liu et al. https://doi.org/10.1016/j.aichem.2024.100062
4015. Seasonalities of Sea Water Properties in Cirebon Waters by Observational Time Series Data Compare to Copernicus Data L. Kurnia Mansur et al. https://doi.org/10.1088/1755-1315/1624/1/012009
4016. Evaluation of Sentinel-2 Vegetation Indices for Estimating Leaf Area Index in Cassava Plots K. Promnikorn et al. https://doi.org/10.3390/agriengineering8040134
4017. Room-level overheating disparities and the limits of passive-design attribution in humid subtropical Australian homes: a year-long field study F. Zhang et al. https://doi.org/10.1016/j.buildenv.2026.114995
4018. Statistical White-Line Analysis in High-Throughput TXM-XANES for Chemical State Quantification J. Wang et al. https://doi.org/10.1021/photonsci.5c00020
4019. Selection of alternate reference evapotranspiration models based on multi-criteria decision ranking for semiarid climate J. Rajput et al. https://doi.org/10.1007/s10668-023-03234-9
4020. Navigating AI-Driven Financial Forecasting: A Systematic Review of Current Status and Critical Research Gaps L. Vancsura et al. https://doi.org/10.3390/forecast7030036
4021. Heavy metal contamination prediction using ensemble model: Case study of Bay sedimentation, Australia S. Bhagat et al. https://doi.org/10.1016/j.jhazmat.2020.123492
4022. Ultrasound imaging with flexible transducers based on real-time and high-accuracy shape estimation X. Gao et al. https://doi.org/10.1016/j.ultras.2024.107551
4023. CVIDS: A Collaborative Localization and Dense Mapping Framework for Multi-Agent Based Visual-Inertial SLAM T. Zhang et al. https://doi.org/10.1109/TIP.2022.3213189
4024. Comparison of High-Resolution Satellite Precipitation Products in Sub-Saharan Morocco M. Rachdane et al. https://doi.org/10.3390/w14203336
4025. Using laboratory-based hyperspectral imaging method to determine carbon functional group distributions in decomposing forest litterfall I. Tahmasbian et al. https://doi.org/10.1016/j.catena.2018.04.023
4026. Investigation of thermal performance in a single-tank multi-layer thermal energy storage system using steel slag combined with alternative filler materials S. Zhang & B. Li https://doi.org/10.1016/j.icheatmasstransfer.2026.111256
4027. Data-driven surrogate modeling for accelerated multiscale FE 2 simulation of nonlinear thermomechanical behavior in composite materials H. Saidi et al. https://doi.org/10.1177/00219983261432304
4028. Applying Bayesian Optimization for Machine Learning Models in Predicting the Surface Roughness in Single-Point Diamond Turning Polycarbonate V. Nguyen et al. https://doi.org/10.1155/2021/6815802
4029. Deep learning approaches for prediction of adiabatic temperature rise of concrete with complex mixture constituents Y. Jiang et al. https://doi.org/10.1016/j.jobe.2023.106816
4030. Numerical groundwater modelling under changing water abstraction in Weyib watershed, Ethiopia M. Aredo et al. https://doi.org/10.1080/23311916.2023.2283297
4031. Exploring in house glutamate inhibitors of matrix metalloproteinase-2 through validated robust chemico-biological quantitative approaches N. Adhikari et al. https://doi.org/10.1007/s11224-017-1028-6
4032. Makine öğrenmesi ve derin öğrenme yöntemleri kullanılarak e-perakende sektörüne yönelik talep tahmini M. ACI & G. AYYILDIZ DOĞANSOY https://doi.org/10.17341/gazimmfd.944081
4033. Lithium enrichment in geothermal systems of the Tibetan Plateau: A coupled machine learning–geochemistry framework for mechanism and prediction S. Wei et al. https://doi.org/10.1016/j.earscirev.2026.105604
4034. Building Agent-Based Decision Support Systems for Word-of-Mouth Programs. A Freemium Application M. Chica https://doi.org/10.2139/ssrn.2821171
4035. Necessity of making water smart for proactive informed decisive actions: A case study of the upper vaal catchment, South Africa A. du Plessis https://doi.org/10.1016/j.envc.2021.100100
4036. Evaluation of potential changes in landslide susceptibility and landslide occurrence frequency in China under climate change Q. Lin et al. https://doi.org/10.1016/j.scitotenv.2022.158049
4037. Smart Polymeric Liners for Internal Corrosion Control in Wet Sour Gas Pipelines: Integrating Nanostructured Materials and AI-Driven Predictive Modelling M. Okyere https://doi.org/10.25082/RIMA.2026.01.005
4038. Projected changes in surface air temperature over Pakistan under bias-constrained CMIP6 models R. Karim et al. https://doi.org/10.1007/s12517-023-11243-1
4039. Carbon fluxes over passively restored Great Fish Thicket, South Africa, reveal modest sequestration during drier rainfall years O. Gwate et al. https://doi.org/10.2989/10220119.2026.2655194
4040. The Prediction of the Gas Utilization Ratio based on TS Fuzzy Neural Network and Particle Swarm Optimization S. Zhang et al. https://doi.org/10.3390/s18020625
4041. A regional analysis model of maize kernel moisture L. Li et al. https://doi.org/10.1002/agj2.20532
4042. Analysis of Radiosonde Temperature Profile Measurement in Pamengpeuk S. Rahayu et al. https://doi.org/10.1088/1742-6596/1373/1/012003
4043. An embedding and interactions learning approach for ID feature in deep recommender system S. Zhang et al. https://doi.org/10.1016/j.eswa.2022.118425
4044. Predicting Energy-Based CO2 Emissions in the United States Using Machine Learning: A Path Toward Mitigating Climate Change L. Tian et al. https://doi.org/10.3390/su17072843
4045. Quantitative Assessment of the Airway Response to Bronchial Tests Based on a Spirometric Curve Shift A. Polak et al. https://doi.org/10.1109/TBME.2020.3004907
4046. Influence of Carob Flour and Carob Bean Gum on Rheological Properties of Cocoa and Carob Pastry Fillings M. Benković et al. https://doi.org/10.3390/foods8020066
4047. The risk assessment of arsenic contamination in the urbanized coastal aquifer of Rayong groundwater basin, Thailand using the machine learning approach N. Sumdang et al. https://doi.org/10.1016/j.ecoenv.2023.114665
4048. Impact of COVID-19 Disease Control Committee (CDCC) policies on prevention of the disease using Bayes network inference in west of Iran A. Soltanian et al. https://doi.org/10.1186/s12889-023-16879-y
4049. Integrated Compensation and Rotation Alignment for Three-Axis Magnetic Sensors Array Q. Li et al. https://doi.org/10.1109/TMAG.2018.2860950
4050. Comparative Analysis of Spatiotemporal Variability of Groundwater Storage in Iraq Using GRACE Satellite Data H. Mohammed et al. https://doi.org/10.3390/hydrology12040069
4051. Evaluation of differences between gridded precipitation products in the Southern Prairies of Manitoba O. Mohammadiigder et al. https://doi.org/10.1016/j.ejrh.2025.102786
4052. Machine Learning-Based Regression Modeling of Compressive Strength Behavior in RESIN8 Recycled Concrete Containing Organic Contamination T. Kashiwao et al. https://doi.org/10.3390/su18189477
4053. New Target for Accurate Terrestrial Laser Scanning and Unmanned Aerial Vehicle Point Cloud Registration T. Urbančič et al. https://doi.org/10.3390/s19143179
4054. Deep synergetic spiking neural P systems for the overall survival time prediction of glioblastoma patients X. Yin et al. https://doi.org/10.1016/j.eswa.2023.123032
4055. A study on water quality prediction by a hybrid CNN-LSTM model with attention mechanism Y. Yang et al. https://doi.org/10.1007/s11356-021-14687-8
4056. Decision support model for the selection of asphalt wearing courses in highly trafficked roads D. Jato-Espino et al. https://doi.org/10.1007/s00500-018-3136-7
4057. Development of a Light and Accurate Nox Prediction Model for Diesel Engines Using Machine Learning and Xai Methods J. Park et al. https://doi.org/10.1007/s12239-023-0047-0
4058. Predicting the Building Stone Cutting Rate Based on Rock Properties and Device Pullback Amperage in Quarries Using M5P Model Tree S. Almasi et al. https://doi.org/10.1007/s10706-017-0177-0
4059. Performance of global climate models in assessing the Indian monsoon: A systematic evaluation Y. Dash et al. https://doi.org/10.1016/j.pce.2026.104565
4060. A Graphical–Analytical Framework for Single-Diode Model Identification Using Datasheet I–V Curves M. Heredia-Rios et al. https://doi.org/10.3390/pr14152479
4061. Shear strength of SFRCB without stirrups simulation: implementation of hybrid artificial intelligence model A. Al-Musawi et al. https://doi.org/10.1007/s00366-018-0681-8
4062. Explainable machine learning for urban housing prices: Policy relevant diagnostics across three cities Y. Noh & C. Park https://doi.org/10.1016/j.cities.2026.107266
4063. Machine Learning for Silver Nanoparticle Electron Transfer Property Prediction B. Sun et al. https://doi.org/10.1021/acs.jcim.7b00272
4064. Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation A. Armanuos et al. https://doi.org/10.3390/atmos11040389
4065. Energy Load Forecasting with Machine Learning: Models, Metrics, and Future Directions M. Manzoor https://doi.org/10.70389/PJAI.100018
4066. Technology evolution in maritime autonomous systems: A patent-based analysis M. Belabyad et al. https://doi.org/10.1016/j.ocecoaman.2025.107744
4067. Application of machine learning in polymer additive manufacturing: A review T. Nasrin et al. https://doi.org/10.1002/pol.20230649
4068. State of art and emerging trends on group recommender system: a comprehensive review S. Singhal & K. Pal https://doi.org/10.1007/s13735-024-00329-5
4069. Short-term electricity consumption forecasting with deep learning E. Demir & S. Gunal https://doi.org/10.1007/s11227-025-07564-5
4070. Landscape Metrics as Ecological Indicators for PM10 Prediction in European Cities S. Sohrab et al. https://doi.org/10.3390/land13122245
4071. Using Mid-Infrared Spectroscopy to Optimize Throughput and Costs of Soil Organic Carbon and Nitrogen Estimates: An Assessment in Grassland Soils P. Ramírez et al. https://doi.org/10.3390/environments9120149
4072. A New Missing Data Imputation Algorithm Applied to Electrical Data Loggers C. Crespo Turrado et al. https://doi.org/10.3390/s151229842
4073. Comparative analysis of 16S rRNA of bacteria associated with the ancient annelid Platynereis dumerilii: structural conservation across clades J. Buenaluz et al. https://doi.org/10.71336/jabs.1510
4074. Activated carbon paper as ethylene adsorber . Qanytah et al. https://doi.org/10.1515/npprj-2022-0082
4075. Utilizing Satellite Imagery for Seasonal Trophic Analysis in the Freshwater Reservoir R. Rachmadita et al. https://doi.org/10.47352/jmans.2774-3047.188
4076. Development of a Long-Range Hydrological Drought Prediction Framework Using Deep Learning M. Khan & R. Maity https://doi.org/10.1007/s11269-024-03735-w
4077. A spatial explicit agent based model approach to evaluate the performance of different monitoring options for mortality estimates in the scope of onshore windfarm impact assessments M. Santos et al. https://doi.org/10.1016/j.ecolind.2016.09.044
4078. FORECASTING CURRENT EXCHANGE AND GOLD RATES WITH HYBRID MODELS USING TIME SERIES AND DEEP LEARNING ALGORITHMS G. Çınarer https://doi.org/10.46519/ij3dptdi.1633193
4079. Diagnosis of depression based on facial multimodal data N. Jin et al. https://doi.org/10.3389/fpsyt.2025.1508772
4080. Winter wheat yield prediction using linear and nonlinear machine learning algorithms based on climatological and remote sensing data M. Haseeb et al. https://doi.org/10.1016/j.inpa.2025.02.004
4081. Numerical modelling of storm tides in the Estuarine System of Santos, São Vicente and Bertioga (SP, Brazil) M. Ruiz et al. https://doi.org/10.1016/j.rsma.2021.101791
4082. Comparative analysis of AI models for cost prediction and feature importance in construction S. Ashrafi et al. https://doi.org/10.1108/JEDT-04-2026-0257
4083. Daily scale evapotranspiration prediction over the coastal region of southwest Bangladesh: new development of artificial intelligence model L. Ye et al. https://doi.org/10.1007/s00477-021-02055-4
4084. Deep-learning-based real-time individualization for reduce-order haemodynamic model B. Li et al. https://doi.org/10.1016/j.compbiomed.2024.108476
4085. Combining machine learning and metaheuristics optimizing for 3PLs’ daily payment schedules in logistics S. Uymaz et al. https://doi.org/10.1016/j.jestch.2026.102436
4086. An Efficient and Interpretable Stacked Model for Wind Speed Estimation Based on Ensemble Learning Algorithms A. Jha et al. https://doi.org/10.1002/ente.202301188
4087. A comprehensive comparison and accuracy of different methods to obtain mean radiant temperature in indoor environment M. Özbey & C. Turhan https://doi.org/10.1016/j.tsep.2022.101295
4088. Geologically deep learning for high-resolution sparse 3D oil reservoir modeling S. Hu et al. https://doi.org/10.1016/j.egyai.2026.100731
4089. AI-BASED ENERGY FORECASTING AND IMPROVED DEMAND MANAGEMENT IN SMART HOMES A. Tokhmetov et al. https://doi.org/10.55452/1998-6688-2026-23-2-133-149
4090. Ethanol production in a biofilm reactor with non-sterile carob extract media and its modeling M. Germec et al. https://doi.org/10.1080/15567036.2018.1511643
4091. Cotton Ginning Rate Prediction Model Development for Commercial Gins: Impact of Variety, Quality, and Moisture Content J. Tumuluru et al. https://doi.org/10.56454/QOHS1717
4092. Deep learning-based stock market forecasting: A comparative analysis of ANN, CNN, and LSTM C. C. M. et al. https://doi.org/10.21511/imfi.23(2).2026.17
4093. The impact of climate change on snowfall in Iran Basins using the satellite-derived snow products and CMIP6 Bias Corrected model H. Ahmadi et al. https://doi.org/10.1007/s00704-022-04302-2
4094. OCLE: A European open access database on climate change effects on littoral and oceanic ecosystems C. de la Hoz et al. https://doi.org/10.1016/j.pocean.2018.09.021
4095. Prediction of Wastewater Treatment Plant Effluent Water Quality Using Recurrent Neural Network (RNN) Models P. Wongburi & J. Park https://doi.org/10.3390/w15193325
4096. HSPEI: A 1‐km spatial resolution SPEI dataset across the Chinese mainland from 2001 to 2022 H. Xia et al. https://doi.org/10.1002/gdj3.276
4097. Techniques and productivity of coppice harvesting operations in Europe: a meta-analysis of available data R. Spinelli et al. https://doi.org/10.1007/s13595-016-0578-x
4098. Traffic Noise Modelling Using Land Use Regression Model Based on Machine Learning, Statistical Regression and GIS A. Adulaimi et al. https://doi.org/10.3390/en14165095
4099. Performance improvement of integrated CO2 systems with HVAC and hot water for hotels S. Smitt et al. https://doi.org/10.1016/j.tsep.2021.100869
4100. ETo‐Brazil: A Daily Gridded Reference Evapotranspiration Data Set for Brazil (2000–2018) D. Althoff et al. https://doi.org/10.1029/2020WR027562
4101. Machine Learning in Wear Prediction R. Shah et al. https://doi.org/10.1115/1.4066865
4102. Intelligent Cluster Head Selection for Energy-Efficient Wireless Sensor Networks: An MLP-Based Approach F. Sanhaji et al. https://doi.org/10.1007/s11277-024-11700-4
4103. Hybrid deep learning models for daily river discharge prediction: lead-time performance analysis in Mymensingh, Bangladesh M. Islam et al. https://doi.org/10.2166/wpt.2025.184
4104. Satellite-based phenology products and in-situ pollen dynamics: A comparative assessment L. Li et al. https://doi.org/10.1016/j.envres.2021.111937
4105. Predicting Ili River streamflow change and identifying the major drivers with a novel hybrid model S. Liu et al. https://doi.org/10.1016/j.ejrh.2024.101807
4106. Quantifying long-term variability of precipitation and temperature over Zambia B. Libanda et al. https://doi.org/10.1016/j.jastp.2020.105201
4107. Comparative analysis of photovoltaic system technologies using advanced Machine Learning algorithms M. Ezzini et al. https://doi.org/10.1088/1402-4896/ae5359
4108. Towards improved agricultural water accounting: a fusion method for regional pond water storage assessment Q. Wang et al. https://doi.org/10.2166/wcc.2026.460
4109. Dominant Factor Analysis and Threshold Inflection Point Determination in Deep Learning-Based SWAT-LSTM Training Models with SHAP Interpretability Analysis J. Tian et al. https://doi.org/10.3390/w18080960
4110. Effect of bypass duct size on the opening pressure of fire doors in an escape tunnel K. Zhong et al. https://doi.org/10.1016/j.tust.2025.107139
4111. A Diffusion-based Deep Learning Approach for the Super-resolution of SDO/HMI Magnetograms Using Hinode/SOT Data C. Sun et al. https://doi.org/10.3847/1538-4357/ae8262
4112. Airfield Incursion Modeling of United States Hub Airports B. Claros et al. https://doi.org/10.2514/1.D0044
4113. The drift handling framework for open radio access networks: An experimental evaluation V. Gudepu et al. https://doi.org/10.1016/j.comnet.2024.110290
4114. High-resolution root-zone soil moisture for agricultural drought assessment using Sentinel-2 and hybrid modeling in the Lake Tana Basin, Ethiopia H. Eshetie et al. https://doi.org/10.1016/j.rsase.2026.101900
4115. Applying wavelet transformation and artificial neural networks to develop forecasting-based reservoir operating rule curves S. Ashrafi et al. https://doi.org/10.1080/02626667.2020.1784902
4116. A Rapid Scalable Embedding and Mapping Model for Recommendation S. Zhang et al. https://doi.org/10.1109/ACCESS.2020.3000894
4117. Intelligent Data-Driven Decision-Making Method for Dynamic Multisequence: An E-Seq2Seq-Based SCUC Expert System N. Yang et al. https://doi.org/10.1109/TII.2021.3107406
4118. Impact of lag window configuration on next-day river water stage forecasting accuracy: comparative evaluation of six machine learning and deep learning algorithms M. Islam et al. https://doi.org/10.2166/h2oj.2026.042
4119. Influence of Thermal Pretreatment on Lignin Destabilization in Harvest Residues: An Ensemble Machine Learning Approach Đ. Kovačić et al. https://doi.org/10.3390/agriengineering6010011
4120. Assessing agreement and usability of kinematic measures between markerless and marker-based motion capture systems during jumping activities S. Kwak et al. https://doi.org/10.1016/j.jbiomech.2025.113065
4121. Mapping Dermatology Life Quality Index (DLQI) scores to EQ-5D utility scores using data of patients with atopic dermatitis from the National Health and Wellness Study A. Vilsbøll et al. https://doi.org/10.1007/s11136-020-02499-1
4122. Counting and locating high-density objects using convolutional neural network M. de Arruda et al. https://doi.org/10.1016/j.eswa.2022.116555
4123. Assessing the stability of terrestrial water storage to drought based on CMIP6 forcing scenarios W. Wei et al. https://doi.org/10.1016/j.jhydrol.2024.132232
4124. Determining the contribution of environmental factors in controlling dust pollution during cold and warm months of western Iran using different data mining algorithms and game theory Z. Ebrahimi-Khusfi et al. https://doi.org/10.1016/j.ecolind.2021.108287
4125. A Deep Learning Approach to Urban Street Functionality Prediction Based on Centrality Measures and Stacked Denoising Autoencoder F. Noori et al. https://doi.org/10.3390/ijgi9070456
4126. Prediction of Safety Risk Levels of Benzopyrene Residues in Edible Oils in China Based on the Variable-Weight Combined LSTM-XGBoost Prediction Model C. Hao et al. https://doi.org/10.3390/foods12112241
4127. Klobuchar, NeQuickG, BDGIM, GLONASS, IRI-2016, IRI-2012, IRI-Plas, NeQuick2, and GEMTEC Ionospheric Models: A Comparison in Total Electron Content and Positioning Domains Y. Yasyukevich et al. https://doi.org/10.3390/s23104773
4128. Topology-regularized universal vector autoregression for traffic forecasting in large urban areas F. Schimbinschi et al. https://doi.org/10.1016/j.eswa.2017.04.015
4129. A Survey on Data-Driven Runoff Forecasting Models Based on Neural Networks Z. Sheng et al. https://doi.org/10.1109/TETCI.2023.3259434
4130. Soil total suction sensing using fiber-optic technology J. Guo et al. https://doi.org/10.1016/j.geoderma.2023.116687
4131. TRNet: A trend and residual network utilizing novel hilly attention mechanism for wind speed prediction in complex scenario P. Shi et al. https://doi.org/10.1016/j.energy.2024.133103
4132. Regionalized ensemble estimation of wave periods for assessing wave energy resources across Canada. Part I: Improved wave-period modelling methodology C. Dong et al. https://doi.org/10.1016/j.ocecoaman.2024.107382
4133. Structural changes to forests during regeneration affect water flux partitioning, water ages and hydrological connectivity: Insights from tracer-aided ecohydrological modelling A. Neill et al. https://doi.org/10.5194/hess-25-4861-2021
4134. Prediction And Analysis Of Concrete Compressive Strength By Machine Learning Methods R. Gürfidan & K. Erten https://doi.org/10.17798/bitlisfen.1816694
4135. Logistic and CSG Growth Models for Predicting Life Expectancy B. Çığşar et al. https://doi.org/10.53433/yyufbed.1432156
4136. Machine Learning Integration in Computational Fluid Dynamics for Turbulence Modeling A. Naseem et al. https://doi.org/10.59324/ejaset.2025.3(1).02
4137. Creating the Slider Tester Repair Recommendation System to Enhance the Repair Step by Using Machine Learning R. Udomsup et al. https://doi.org/10.3390/machines12090661
4138. Exploratory framework for analysing road traffic accident data with validation on Gauteng province data T. Makaba et al. https://doi.org/10.1080/23311916.2020.1834659
4139. A Systematic Study on a Customer’s Next-Items Recommendation Techniques Q. Ilyas et al. https://doi.org/10.3390/su14127175
4140. Near future flash flood prediction in an arid region under climate change G. Al-Rawas et al. https://doi.org/10.1038/s41598-024-76232-0
4141. Algorithms to mimic human interpretation of turbidity events from drinking water distribution systems K. Gleeson et al. https://doi.org/10.2166/hydro.2023.159
4142. Evaluation of Sentinel 1–derived and open-access digital elevation model products in mountainous areas of Western Ghats, India S. Devaraj & K. Yarrakula https://doi.org/10.1007/s12517-020-06108-w
4143. Vulnerability assessment of aerosol and climate variability for rice and maize yield using EO datasets for sustainable agriculture over India D. Gupta et al. https://doi.org/10.1007/s10661-024-12862-1
4144. MorphFlow: Estimating Motion in In-Situ Tests of Concrete T. Nogatz et al. https://doi.org/10.1007/s11340-024-01104-7
4145. Comparison of regression models of linear and polynomial dependencies in moisture detection technique A. Futa et al. https://doi.org/10.1088/1742-6596/2628/1/012005
4146. A theoretical model developed for predicting nail withdrawal load from wood by mechanics Y. Wang & S. Lee https://doi.org/10.1007/s00107-017-1227-2
4147. Accuracy assessment of ALOS World 3D-30m DEMs using field data from Lagos and Federal Capital Territory, Nigeria C. Okolie & I. Arungwa https://doi.org/10.1080/10106049.2022.2060320
4148. Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data R. dos Santos https://doi.org/10.1016/j.jag.2020.102066
4149. Development of a soil wetting pattern estimation model for drip irrigation Y. Li et al. https://doi.org/10.2166/ws.2022.429
4150. INVESTIGATION of PHYSICAL RISK FACTORS in NATURAL STONE QUARRIES AND ESTIMATION OF PM CONCENTRATIONS WITH M5P DECISION TREE T. Doğan et al. https://doi.org/10.36306/konjes.1727780
4151. Closure and uncertainty assessment for ocean color reflectance using measured volume scattering functions and reflective tube absorption coefficients with novel correction for scattering A. Tonizzo et al. https://doi.org/10.1364/AO.56.000130
4152. Physically Based Soap Bubble Synthesis for VR S. Yoo et al. https://doi.org/10.3390/app11073090
4153. Region-guided preprocessing and U-Net variants for improved panoramic dental radiograph segmentation N. Sogur & N. Çerçevik https://doi.org/10.1016/j.bspc.2026.110068
4154. Gene expression programming (GEP) as novel tool for thermal analysis and kinetic modeling of pyrolysis reactions: coal pyrolysis case study H. Najafi et al. https://doi.org/10.1108/EC-04-2023-0153
4155. Estimation of Real-World Fuel Consumption Rate of Light-Duty Vehicles Based on the Records Reported by Vehicle Owners I. Zeng et al. https://doi.org/10.3390/en14237915
4156. Dynamic Bayesian Modeling of Carbon-Adjusted Costs and Supply Chain Risks for Sustainable Investment in Power Grid Technical Renovation Projects M. Song et al. https://doi.org/10.3390/math14111921
4157. A Hybrid DDMRP-OUTL Inventory Policy with Defect Prediction for Resilient Supply Chains E. Rosyida et al. https://doi.org/10.25077/josi.v25.n1.p63-93.2026
4158. Machine learning approach for forest biomass modelling with in-situ and remote sensing data in Narmadapuram central India P. Rajput https://doi.org/10.1007/s40808-025-02527-4
4159. Advanced Predictive Structural Health Monitoring in High-Rise Buildings Using Recurrent Neural Networks A. Ghaffari et al. https://doi.org/10.3390/buildings14103261
4160. Predicting Soil Particulate Organic Mattter Using Artificial Neural Network with Wavelet Function P. Baligh et al. https://doi.org/10.1080/00103624.2020.1808012
4161. Identifying the impact of land use land cover change on streamflow and nitrate load following modeling approach: a case study in the upstream Dong Nai River basin, Vietnam T. Le et al. https://doi.org/10.1007/s11356-023-26887-5
4162. A Deep Learning-based Approach to Predict the Flood Patterns Using Sentinel-1A Time Series Images M. Siddique et al. https://doi.org/10.1007/s12524-024-02016-8
4163. Multi-Objective Co-Optimization of Parameters for Sub-Models of Grain and Leaf Growth in Dryland Wheat via the DREAM-zs Algorithm H. Zhu et al. https://doi.org/10.3390/agriculture16010107
4164. Creatinine clearance in critically ill adults: prospective comparison of prediction by intensive care unit physicians and machine learning models G. De Vlieger et al. https://doi.org/10.1007/s00134-024-07557-7
4165. 基于CAD与方向性l0正则化的有限角CT重建 杨. Yang Run et al. https://doi.org/10.3788/AOS251447
4166. Design of an Energy Pile Based on CPT Data Using Soft Computing Techniques P. Kumar & P. Samui https://doi.org/10.3390/infrastructures7120169
4167. Dimensionality reduction technique based phase aberration compensation and spurious fringe removal in off-axis digital holographic microscopy H. Chaudhari et al. https://doi.org/10.1016/j.optlaseng.2023.107853
4168. Age grading An. gambiae and An. arabiensis using near infrared spectra and artificial neural networks M. Milali et al. https://doi.org/10.1371/journal.pone.0209451
4169. Effects of synthesis conditions and release medium pH on release properties of acyclovir – mercaptopropyl modified silica composite E. Dolinina et al. https://doi.org/10.1080/03639045.2022.2037627
4170. Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites H. Post et al. https://doi.org/10.1002/2015JG003297
4171. Artificial neural network modeling for predicting mechanical properties of Mediterranean green composites M. Hayajneh et al. https://doi.org/10.1088/2631-6331/ae9824
4172. Prediction of Yangtze River streamflow based on deep learning neural network with El Niño–Southern Oscillation S. Ha et al. https://doi.org/10.1038/s41598-021-90964-3
4173. Multimodal image registration techniques: a comprehensive survey H. Velesaca et al. https://doi.org/10.1007/s11042-023-17991-2
4174. Developing A Mathematical Model for Planning Repetitive Construction Projects By Using Support Vector Machine Technique A. Burhan et al. https://doi.org/10.2478/cee-2021-0039
4175. Calibration for Improving the Medium-Range Soil Forecast over Central Tibet: Effects of Objective Metrics’ Diversity Y. Guo et al. https://doi.org/10.3390/atmos15091107
4176. Predicting Learning Achievement Using Big Data Cluster Analysis : Focusing on Longitudinal Study S. Ko https://doi.org/10.9728/dcs.2018.19.9.1769
4177. A Graph Convolutional Stacked Bidirectional Unidirectional-LSTM Neural Network for Metro Ridership Prediction P. Chen et al. https://doi.org/10.1109/TITS.2021.3065404
4178. A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India) B. Pham et al. https://doi.org/10.1016/j.envsoft.2016.07.005
4179. Detection of Foliar Phosphorus in Potato Crops Using Multispectral Imagery E. de Oliveira et al. https://doi.org/10.1007/s11540-025-10001-y
4180. Online prediction of dense medium suspension density based on phase space reconstruction X. Sun et al. https://doi.org/10.1080/02726351.2017.1333180
4181. Prediction of Length of Stay on the Intensive Care Unit Based on Least Absolute Shrinkage and Selection Operator C. Li et al. https://doi.org/10.1109/ACCESS.2019.2934166
4182. Accurate deep-learning estimation of chlorophyll-a concentration from the spectral particulate beam-attenuation coefficient S. Graban et al. https://doi.org/10.1364/OE.397863
4183. Deciphering the performance of satellite-based daily rainfall products over Zambia B. Libanda et al. https://doi.org/10.1007/s11600-020-00429-w
4184. Salmonella in raw lamb liver: experimental growth kinetics and a quantitative microbial risk assessment from evisceration to consumption Z. Qadiry et al. https://doi.org/10.1016/j.fbio.2026.108885
4185. Atmospheric circulation patterns as the driver of Caspian Sea level variability S. Moghim et al. https://doi.org/10.1007/s00382-026-08360-4
4186. A new crude oil futures forecasting method based on fusing quadratic forecasting with residual forecasting M. Su et al. https://doi.org/10.1016/j.dsp.2022.103691
4187. A Self-Localization Algorithm for Mobile Targets in Indoor Wireless Sensor Networks Using Wake-Up Media Access Control Protocol R. Souissi et al. https://doi.org/10.3390/s24030802
4188. Fuzzy Ensemble Clustering Approach to Address Regionalization Uncertainties in Flood Frequency Analysis K. Kiran & V. Srinivas https://doi.org/10.1029/2020WR028412
4189. Higher than expected N2O emissions from soybean crops in the Pampas Region of Argentina: Estimates from DayCent simulations and field measurements T. Della Chiesa et al. https://doi.org/10.1016/j.scitotenv.2022.155408
4190. Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa S. Sazawal et al. https://doi.org/10.7189/jogh.12.04021
4191. Local Scaffold Diversity-Contributed Generator for Discovering Potential NLRP3 Inhibitors W. Bo et al. https://doi.org/10.1021/acs.jcim.3c01818
4192. Machine learning models to estimate the elastic modulus of weathered magmatic rocks N. Ceryan et al. https://doi.org/10.1007/s12665-021-09738-9
4193. Physics-informed neural network with damage mechanics embedding for crack-width prediction in cable-stayed bridges X. Liu et al. https://doi.org/10.1016/j.engstruct.2026.122602
4194. Missing-aware spectral-temporal graph neural networks for robust multivariate time-series forecasting Y. Feng et al. https://doi.org/10.1016/j.neucom.2026.135441
4195. Solar energy production in EU + countries using space–time forecasting A. Grigorescu et al. https://doi.org/10.1007/s00202-025-03389-w
4196. Empirical approach for modelling time-dependent seepage line and improving slope stability predictions of homogeneous river levees M. Öttl et al. https://doi.org/10.1080/23311916.2026.2678633
4197. A modelling approach for Mangrove carbon dynamics using integrated optical and SAR data in Balikpapan Bay, Indonesia: algorithm development and accuracy enhancement A. Suardana et al. https://doi.org/10.1007/s40808-025-02638-y
4198. Design and combinatorial library generation of 1H 1,4 benzodiazepine 2,5 diones as photosystem-II inhibitors: A public QSAR approach P. Banjare et al. https://doi.org/10.1016/j.bjbas.2017.04.003
4199. Downscaling of TRMM3B43 Product Through Spatial and Statistical Analysis Based on Normalized Difference Water Index, Elevation, and Distance From Sea H. Ezzine et al. https://doi.org/10.1109/LGRS.2017.2705430
4200. Wind power 24-h ahead forecast by an artificial neural network and an hybrid model: Comparison of the predictive performance E. Ogliari et al. https://doi.org/10.1016/j.renene.2021.06.108
4201. Broad Siamese Network for Facial Beauty Prediction Y. Li et al. https://doi.org/10.1109/TAI.2024.3429293
4202. Improving Nighttime Light Imagery With Location-Based Social Media Data N. Zhao et al. https://doi.org/10.1109/TGRS.2018.2871788
4203. Risk Assessment for Linear Regression Models in Metrology D. Božić et al. https://doi.org/10.3390/app14062605
4204. AI Judges in Design: Toward Expert-Equivalent Design Evaluations With Vision-Language Models and In-Context Learning K. Edwards et al. https://doi.org/10.1115/1.4071835
4205. Predictive model for growth of Clostridium botulinum from spores at temperatures applicable to cooling of cooked ground pork V. Juneja et al. https://doi.org/10.1016/j.ifset.2022.102960
4206. Investigating the efficacy of a new symmetric index of agreement for evaluating WRF simulated summer monsoon rainfall over northeast India A. Chakravorty et al. https://doi.org/10.1007/s00703-020-00761-2
4207. High-Resolution Daily XCH4 Prediction Using New Convolutional Neural Network Autoencoder Model and Remote Sensing Data M. Awad & S. Homayouni https://doi.org/10.3390/atmos16070806
4208. Laboratory Research on Polarized Optical Properties of Saline-Alkaline Soil Based on Semi-Empirical Models and Machine Learning Methods Q. Gu et al. https://doi.org/10.3390/rs14010226
4209. Predicting the accurate period of true dawn using a third-degree polynomial model T. Saksono & M. Fulazzaky https://doi.org/10.1080/20909977.2020.1738106
4210. Toward fine-scale microwave monitoring of dryland vegetation: an alternative high spatial resolution vegetation optical depth retrieval algorithm from Sentinel-1 over the Sahel region Z. Lu et al. https://doi.org/10.1016/j.rse.2026.115675
4211. Machine learning-assisted development of gas separation membranes: A review A. Li et al. https://doi.org/10.1016/j.ccst.2025.100374
4212. A novel committee-based framework for modeling groundwater level fluctuations: A combination of mathematical and machine learning models using the weighted multi-model ensemble mean algorithm A. Mazraeh et al. https://doi.org/10.1016/j.gsd.2023.101062
4213. Multi-objective ventilation optimization for indoor air quality, thermal comfort, and energy conservation in the post-pandemic era: A case study for a moving elevator D. Mei et al. https://doi.org/10.1063/5.0212810
4214. Predicting the Properties of Construction Concrete Modified with a Nanopreparation and Containing E-Waste Plastic R. Sapinov et al. https://doi.org/10.3390/recycling11060105
4215. A graph clustering neural network framework for mapping urban functional zones in a fast-evolving urban landscape of Bangladesh M. Haydar et al. https://doi.org/10.1016/j.cacint.2026.100401
4216. Began+: Leveraging bi-temporal SAR-optical data fusion to reconstruct clear-sky satellite imagery under large cloud cover Y. Xia et al. https://doi.org/10.1016/j.rse.2025.115171
4217. Simulation of Hydrocarbon Concentration Spatial Distribution in the Bohai Sea Using Chebyshev-Based Orthogonal Polynomial Fitting 书. 郭 https://doi.org/10.12677/aam.2026.151021
4218. An automated and explainable machine learning framework for multi-objective energy performance evaluation and early-stage design support of indoor arenas Y. Wang et al. https://doi.org/10.1016/j.engappai.2026.114753
4219. Future Projection with an Extreme-Learning Machine and Support Vector Regression of Reference Evapotranspiration in a Mountainous Inland Watershed in North-West China Z. Yin et al. https://doi.org/10.3390/w9110880
4220. Phase correction based measurement enhancement for Φ-OTDR under noisy conditions Y. Shi et al. https://doi.org/10.1016/j.optlaseng.2025.109466
4221. Systematic evaluation of supervised machine learning for sample origin prediction using metagenomic sequencing data J. Chen & A. Tyler https://doi.org/10.1186/s13062-020-00287-y
4222. Exploring happiness factors with explainable ensemble learning in a global pandemic M. Hamja et al. https://doi.org/10.1371/journal.pone.0313276
4223. Prediction of biogas production rate from anaerobic hybrid reactor by artificial neural network and nonlinear regressions models F. Tufaner & Y. Demirci https://doi.org/10.1007/s10098-020-01816-z
4224. A Computational Intelligence Approach to Predict Energy Demand Using Random Forest in a Cloudera Cluster L. Cáceres et al. https://doi.org/10.3390/app11188635
4225. Machine learning-assisted prediction and optimization of electrocatalytic activity H. Song et al. https://doi.org/10.1016/j.jmst.2025.04.050
4226. Multimodal Disentangled Dynamic Fusion for Short-Term Multimodal Travel Demand Forecasting S. Liu et al. https://doi.org/10.3390/smartcities9090147
4227. Cross-sensor data reconstruction for optical remote sensing gap-filling with attention-enhanced multi-scale fusion network X. Wang et al. https://doi.org/10.1016/j.jag.2025.104571
4228. Real-Time Visual–Inertial SLAM Based on Adaptive Keyframe Selection for Mobile AR Applications J. Piao & S. Kim https://doi.org/10.1109/TMM.2019.2913324
4229. Large Language Models in Power Systems: A Survey on Applications and Fine-Tuning B. Sun et al. https://doi.org/10.23919/CJEE.2026.000040
4230. Enhancing Short-Term Electric Load Forecasting for Households Using Quantile LSTM and Clustering-Based Probabilistic Approach Z. Masood et al. https://doi.org/10.1109/ACCESS.2024.3406439
4231. Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment Z. Yin et al. https://doi.org/10.1007/s00477-018-1585-2
4232. Data-Driven Soft Sensor for Hot Strip Mill Process Based on Multiscale Information-Fusion Attention Network J. Xue et al. https://doi.org/10.1109/TIM.2024.3450083
4233. Remote sensing reconstruction of long-term water level and storage variations of a poorly-gauged river in the Tibetan Plateau L. Ke et al. https://doi.org/10.1016/j.ejrh.2022.101020
4234. Vertical Profile of Wind Diurnal Cycle in the Surface Boundary Layer over the Coast of Cotonou, Benin, under a Convective Atmosphere H. Donnou et al. https://doi.org/10.1155/2019/7530828
4235. Efficiency of coupled invasive weed optimization-adaptive neuro fuzzy inference system method to assess physical habitats in streams M. Sedighkia & A. Abdoli https://doi.org/10.1007/s42452-021-04203-5
4236. A hybrid hydrodynamic and machine learning framework for coastal erosion and sedimentation prediction M. Elshaarawy et al. https://doi.org/10.1007/s12145-026-02274-9
4237. Predicting Household Electric Power Consumption Using Multi-step Time Series with Convolutional LSTM L. Cascone et al. https://doi.org/10.1016/j.bdr.2022.100360
4238. Comparison of Empirical ETo Relationships with ERA5-Land and In Situ Data in Greece N. Gourgouletis et al. https://doi.org/10.3390/geographies3030026
4239. Enhancing seabed sediment classification with multibeam echo-sounding and self-training: a case study from the East Sea of South Korea C. Lee et al. https://doi.org/10.3389/feart.2025.1550244
4240. S&P500 volatility analysis using high-frequency multipower variation volatility proxies W. Chin & M. Lee https://doi.org/10.1007/s00181-017-1345-z
4241. Development of the grass LAI and CCC remote sensing-based models and their transferability using sentinel-2 data in heterogeneous grasslands P. Tsele et al. https://doi.org/10.1080/01431161.2023.2205982
4242. Single Image Dehazing Based on Haze Prior Residual Perception Learning K. Wang et al. https://doi.org/10.1007/s00034-025-03058-0
4243. Multimodal learning for early prediction of COVID-19 outbreaks J. Kim et al. https://doi.org/10.1016/j.ipm.2025.104562
4244. Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition R. Prasad et al. https://doi.org/10.1016/j.geoderma.2018.05.035
4245. Comparison of Climate Model Large Ensembles With Observations in the Arctic Using Simple Neural Networks Z. Labe & E. Barnes https://doi.org/10.1029/2022EA002348
4246. Revolutionizing inverse design of ionic liquids through the multi-property prediction of over 300,000 novel variants using ensemble deep learning T. Lemaoui et al. https://doi.org/10.1016/j.mser.2024.100798
4247. A hybrid molecular dynamics–machine learning framework for boiling point estimation in aromatic fluids A. Shateri et al. https://doi.org/10.1016/j.csite.2025.106684
4248. Forecasting the Development of Offshore Wind Energy in Poland in the Context of the Energy Transformation and Sustainable Development Goals A. Rybak et al. https://doi.org/10.3390/en18205380
4249. A comparative analysis of classical and machine learning methods for forecasting TB/HIV co-infection A. Abade et al. https://doi.org/10.1038/s41598-024-69580-4
4250. Afforestation as a mitigation strategy: countering climate-induced risk of forest carbon sink in China Y. Cao et al. https://doi.org/10.1186/s13021-025-00308-1
4251. Field scale wheat yield prediction using ensemble machine learning techniques S. Gawdiya et al. https://doi.org/10.1016/j.atech.2024.100543
4252. Numerical Automated Stiffness Optimization of a Thin Television Back-Cover Module: Research on the Industrial Problem D. Kwon et al. https://doi.org/10.1007/s12541-021-00557-3
4253. Relative assessment of constrained multiple objective optimization techniques for optimal pumping strategy design to mitigate saline water intrusion in coastal groundwater systems D. Roy & B. Datta https://doi.org/10.1016/j.desal.2025.118773
4254. When does seasonal refinement improve stineman interpolation for missing air-quality time series? A similarity-weighted seasonal anchor approach S. Somnugpong https://doi.org/10.1007/s10661-026-15770-8
4255. Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction H. Tao et al. https://doi.org/10.1007/s00521-021-06362-3
4256. Impacts of climate change on extreme weather indices in Ecuadorian cities: A socioeconomic analysis D. Portalanza et al. https://doi.org/10.1016/j.wace.2025.100810
4257. A multi-criteria leave-two-out cross-validation procedure for max-stable process selection G. Nicolet et al. https://doi.org/10.1016/j.spasta.2017.09.004
4258. Improving flood inundation forecasts through the assimilation of in situ floodplain water level measurements based on alternative observation network configurations A. Van Wesemael et al. https://doi.org/10.1016/j.advwatres.2019.05.025
4259. Assessing the Performance of Random Forests for Modeling Claim Severity in Collision Car Insurance Y. Staudt & J. Wagner https://doi.org/10.3390/risks9030053
4260. Discrimination, Social Risk, and Portfolio Choice Y. Bonaparte et al. https://doi.org/10.2139/ssrn.2863351
4261. Tunable optoelectronic properties of Na2MgSnX6 (X = Cl, Br, I) halide double perovskites for photodetector applications: A combined DFT and machine learning study A. Raza et al. https://doi.org/10.1016/j.physb.2026.419377
4262. A deep learning approach for forecasting non-stationary big remote sensing time series M. Rhif et al. https://doi.org/10.1007/s12517-020-06140-w
4263. A novel online sequential extreme learning machine with L2,1-norm regularization for prediction problems . Preeti et al. https://doi.org/10.1007/s10489-020-01890-2
4264. Reinforcing bar development length modeling using integrative support vector regression model with response surface method: New approach B. Keshtegar & Z. Yaseen https://doi.org/10.1016/j.isatra.2021.10.010
4265. End-to-end prediction of skin permeability from SMILES using a hybrid and explainable GNN framework D. Alakuş & T. Alakuş https://doi.org/10.1016/j.jddst.2026.108617
4266. A Hybrid Model of Artificial Neural Network and SARIMA Models for Predicting Inflation Rate Change in Nigeria's Economy D. Bartholomew et al. https://doi.org/10.1007/s40745-025-00656-2
4267. Age estimation through CT image analysis of the thoracic cage in a Mediterranean population M. Partido Navadijo et al. https://doi.org/10.1007/s00414-025-03660-6
4268. Best Practices for Elevation-Based Assessments of Sea-Level Rise and Coastal Flooding Exposure D. Gesch https://doi.org/10.3389/feart.2018.00230
4269. A Novel Method to Analyze the Relationship between Thermoelectric Coefficient and Energy Disorder of Any Density of States in an Organic Semiconductor D. Qin et al. https://doi.org/10.3390/mi14081509
4270. Automated 3D volumetric reconstruction of multiple-room building interiors for as-built BIM J. Jung et al. https://doi.org/10.1016/j.aei.2018.10.007
4271. Spatial Feature-Based Prioritization for Transmission of Point Cloud Data in 3D-Image Sensor Networks M. Oka et al. https://doi.org/10.1109/JSEN.2021.3106963
4272. Relationship between NIR Spectrum and Polymer Particle Size for Monitoring Emulsion Polymerization Processes D. da Silva & R. Giudici https://doi.org/10.1021/acs.iecr.5c02647
4273. Combining deficit irrigation and nutrient amendment enhances the water productivity of tomato (Solanum lycopersicum L.) in the tropics P. Amankwaa-Yeboah et al. https://doi.org/10.3389/fsufs.2023.1199386
4274. Augmentation of Sentiment Analysis Models C. Henshaw et al. https://doi.org/10.3390/electronics15184310
4275. Multidimensional uncertainty in commodity markets: a hybrid deep learning approach for corn futures price forecasting M. Abedin et al. https://doi.org/10.1007/s10479-026-07400-w
4276. Research on Thrips Object Detection and Counting Algorithms in Leaf Backgrounds D. Huang et al. https://doi.org/10.3390/agronomy16171709
4277. Waveform Designs for Integrated Sensing and Communication With Low Probability of Intercept Based on the Cyclic Spectrum Q. Shi et al. https://doi.org/10.1109/TVT.2025.3543223
4278. Comparative Analysis and Modeling of 4G LTE Propagation Using the Okumura-Hata and COST-231 Hata Models, Enhanced with Spatially Correlated Log-Normal Shadowing K. Barry et al. https://doi.org/10.4236/jemaa.2026.1810010
4279. Wake and output power prediction across different types of offshore wind turbines using transfer learning and meta-learning S. Liu & Q. Li https://doi.org/10.1063/5.0259493
4280. Evidence for Soil Phosphorus Resource Partitioning in a Diverse Tropical Tree Community R. Müller et al. https://doi.org/10.3390/f15020361
4281. Stock returns prediction using kernel adaptive filtering within a stock market interdependence approach S. Garcia-Vega et al. https://doi.org/10.1016/j.eswa.2020.113668
4282. Meta-analysis of technologies for diabetes treatment: glycemic control, prediction, meal and physical activity detection T. Koutný et al. https://doi.org/10.1088/2516-1091/ae39b9
4283. A Smart Recommender Based on Hybrid Learning Methods for Personal Well-Being Services R. Nouh et al. https://doi.org/10.3390/s19020431
4284. Generalizability of empirical correlations for predicting higher heating values of biomass M. Daskin et al. https://doi.org/10.1080/15567036.2024.2332472
4285. Identifying effective AE parameters for damage evaluation of concrete in headwork: a combined cluster and random forest analysis of acoustic emission data Y. Shimamoto et al. https://doi.org/10.1007/s10333-022-00910-w
4286. Cylindrical Direct‐Current Triboelectric Nanogenerator with Constant Output Current J. Wang et al. https://doi.org/10.1002/aenm.201904227
4287. Biomass Assessment of Agricultural Crops Using Multi-temporal Dual-Polarimetric TerraSAR-X Data N. Ahmadian et al. https://doi.org/10.1007/s41064-019-00076-x
4288. Fusion of UAV-based DEMs for vertical component accuracy improvement I. Ajibola et al. https://doi.org/10.1016/j.measurement.2019.07.023
4289. A hybrid ensemble learning approach for indoor thermal comfort predictions utilizing the ASHRAE RP-884 database X. Feng et al. https://doi.org/10.1016/j.enbuild.2023.113083
4290. Calibration and validation of FLFArs -- a new flood loss function for Australian residential structures R. Hasanzadeh Nafari et al. https://doi.org/10.5194/nhess-16-15-2016
4291. YÜZ TANIMA SİSTEMLERİNDE DOĞRULUK PERFORMANSLARININ DEĞERLENDİRİLMESİ B. AKSOY https://doi.org/10.21923/jesd.559887
4292. Integrating LiDAR, Multispectral and SAR Data to Estimate and Map Canopy Height in Tropical Forests J. Fagua et al. https://doi.org/10.3390/rs11222697
4293. Industrial computed tomography for three-dimensional cultural relic model reconstruction based on L1-αL2+TV norm minimization H. Zhang et al. https://doi.org/10.1016/j.measurement.2023.114057
4294. Tropical Cyclone Impacts on Headland Protected Bay D. Wishaw et al. https://doi.org/10.3390/geosciences10050190
4295. Impact of Li-Ion Battery on System’s Overall Impedance and Received Signal Strength for Power Line Communication (PLC) V. Marsic et al. https://doi.org/10.3390/s22072634
4296. Extending the Thornthwaite–Mather Water Budget Model for Surface Runoff Estimation: A Nationwide Assessment in Mainland Portugal J. Pegas et al. https://doi.org/10.3390/w18182343
4297. Modelling growth rates and developing an age determination tool for nestling Bonelli's Eagle Aquila fasciata S. Iezekiel et al. https://doi.org/10.1111/aab.70002
4298. Interpretable multi-objective machine learning with calibrated uncertainty for deployment-oriented prediction of defects and properties in polymer FFF E. Asare et al. https://doi.org/10.1016/j.measurement.2025.119350
4299. Assessing the impacts of cover crops on maize and soybean yield in the U.S. Midwestern agroecosystems Z. Qin et al. https://doi.org/10.1016/j.fcr.2021.108264
4300. Machine learning approach for evaluating soil liquefaction probability based on reliability method S. Khatoon et al. https://doi.org/10.1007/s11069-024-06934-1
4301. Geospatial-based surveillance of malaria risk in Dar es Salaam using a hybrid 3DCNN + LSTM and CA model E. Kanjagaile et al. https://doi.org/10.1186/s12942-026-00482-6
4302. Modélisation neuro-floue et optimisation probabiliste d’un échangeur de chaleur à plaques en hydrométallurgie J. MALELA KAZUMBA https://doi.org/10.52497/jitipee.v10i1.422
4303. The UNIFAC model and the partition of alkyl and alkylphenol ethoxylate surfactants in the excess phases of middle phase microemulsions A. Boza Troncoso & E. Acosta https://doi.org/10.1016/j.fluid.2015.03.035
4304. Estimation of Methane Gas Production in Turkey Using Machine Learning Methods G. Ünal Uyar et al. https://doi.org/10.3390/app13148442
4305. Estimating urban LST using multiple remotely sensed spectral indices and elevation retrievals T. Mushore et al. https://doi.org/10.1016/j.scs.2021.103623
4306. Continual multiple adverse weather image restoration based on multi-scale representative knowledge distillation J. Han et al. https://doi.org/10.1007/s13042-026-03217-y
4307. Coseismic landslide runout distance prediction based on hybrid stacking ensemble model H. Qiu et al. https://doi.org/10.1007/s11069-026-08381-6
4308. Soil moisture quantity prediction using optimized neural supported model for sustainable agricultural applications S. Chatterjee et al. https://doi.org/10.1016/j.suscom.2018.09.002
4309. High-resolution gridded population datasets for Latin America and the Caribbean using official statistics T. McKeen et al. https://doi.org/10.1038/s41597-023-02305-w
4310. A vanishing moment ensemble model for wind speed multi-step prediction with multi-objective base model selection H. Liu & Z. Duan https://doi.org/10.1016/j.apenergy.2019.114367
4311. Anomaly Signal Imputation Using Latent Coordination Relations T. Chalongvorachai & K. Woraratpanya https://doi.org/10.1109/ACCESS.2024.3448236
4312. A novel approach to estimate rock deformation under uniaxial compression using a machine learning technique P. T. et al. https://doi.org/10.1007/s10064-024-03775-x
4313. Prediction of groundwater quality assessment by integrating boosted learning with DE optimizer S. Subudhi et al. https://doi.org/10.1038/s41598-025-30122-1
4314. An Empirical Study on V2X Enhanced Low-Cost GNSS Cooperative Positioning in Urban Environments P. Schwarzbach et al. https://doi.org/10.3390/s19235201
4315. Accelerated method for the optimization of quadratic image filter S. Uzun & D. Akgün https://doi.org/10.1117/1.JEI.28.3.033036
4316. Testing methods to estimate spectral reflectance using datasets under different illuminants J. Xu et al. https://doi.org/10.1002/col.22859
4317. Ship Navigation and Fuel Profiling based on Noon Report using Neural Network Generative Modeling J. Hadi et al. https://doi.org/10.1088/1742-6596/2311/1/012005
4318. Spatiotemporal prediction and predictive management of foundation Pit groundwater levels under multi-source disturbance: A data-driven deep learning approach S. Wang et al. https://doi.org/10.1016/j.aej.2026.05.014
4319. Sub-clustering based recommendation system for stroke patient: Identification of a specific drug class for a given patient R. Ceskoutsé et al. https://doi.org/10.1016/j.compbiomed.2024.108117
4320. Thermographic and Machine Learning approaches for a rapid estimation of gears bending fatigue strength L. Corsaro et al. https://doi.org/10.1007/s10010-025-00863-6
4321. Impact of the Russia-Ukraine conflict on the quality and quantity of Malaysia’s palm oil production: A time series analysis A. Mat Enh et al. https://doi.org/10.1371/journal.pone.0302405
4322. Machine Learning-Based Japanese Spot Market Price Forecasting Considering the Solar Contribution X. Fang et al. https://doi.org/10.1109/ACCESS.2024.3387071
4323. Dual Crop Coefficient of Watermelon under Deficit Irrigation, Mulching, and AquaCrop Model Performance in Arba Minch, Ethiopia B. Reta et al. https://doi.org/10.1061/JIDEDH.IRENG-10336
4324. Multi-objective extensive hypothesis testing for the estimation of advanced crash frequency models Z. Ahern et al. https://doi.org/10.1016/j.aap.2024.107690
4325. Improving the Spatial Resolution of GRACE-Derived Terrestrial Water Storage Changes in Small Areas Using the Machine Learning Spatial Downscaling Method Z. Chen et al. https://doi.org/10.3390/rs13234760
4326. Utilization of Multi-Temporal Microwave Remote Sensing Data within a Geostatistical Regionalization Approach for the Derivation of Soil Texture P. Marzahn & S. Meyer https://doi.org/10.3390/rs12162660
4327. Decoupling clinker technology from cement product emissions: A macroeconomic ML–LCA framework for global embodied carbon policy screening D. Kandiyil et al. https://doi.org/10.1016/j.jenvman.2026.130402
4328. Assessing the performance of CMIP6 climate models and future projections of climate variables over the Amhara National Regional State, Ethiopia D. Mengistu et al. https://doi.org/10.1007/s44274-026-00843-9
4329. Effects of initial abstraction ratios in SCS-CN method on runoff prediction of green roofs in a semi-arid region W. Liu et al. https://doi.org/10.1016/j.ufug.2021.127331
4330. Hydrodynamic Model Optimization for Marine Tourism Development Suitability in Vicinity of Poso Regency Coastal Area, Central Sulawesi, Indonesia S. Hermawan et al. https://doi.org/10.3390/su15043150
4331. AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness A. Timtong et al. https://doi.org/10.1016/j.rineng.2024.103289
4332. Kinetic Modeling and Techno-economic Feasibility of Ethanol Production From Carob Extract Based Medium in Biofilm Reactor M. Germec et al. https://doi.org/10.3390/app9102121
4333. Assessment and prediction of the climate change impact on crop yield, in Jimma Zone Upper Gilgel Gibe Districts, Ethiopia C. Sime & T. Demissie https://doi.org/10.1007/s12517-022-09605-2
4334. Optimization of LSTM networks through neuroevolution for drought forecasting in Mexico R. Villegas-Vega et al. https://doi.org/10.1007/s00704-025-05818-z
4335. River water level measurement system using Sobel edge detection method F. Rozaqi & W. Wahyono https://doi.org/10.14710/jtsiskom.2021.14119
4336. Development of Cost Prediction Model for Improving Cost Estimate at Completion of Building Construction Projects Using MATLAB R2014a Simulink, and Regression Model G. Ayalew & G. Ayalew https://doi.org/10.11648/j.ijmfs.20251102.12
4337. How velocity impacts eccentric force generation of fully activated skinned skeletal muscle fibers in long stretches S. Weidner et al. https://doi.org/10.1152/japplphysiol.00735.2021
4338. Regression Modeling for Prediction of Earned Value Indexes in Public Building Construction Projects: The case of Ethiopia G. Ayalew et al. https://doi.org/10.1080/23311916.2023.2220497
4339. The Use of Multisource Optical Sensors to Study Phytoplankton Spatio-Temporal Variation in a Shallow Turbid Lake M. Bresciani et al. https://doi.org/10.3390/w12010284
4340. Examining System-Wide Bike-Share Ridership in Response to Bikeway Expansion: A Trend-Based Analysis M. Azimi et al. https://doi.org/10.1061/JTEPBS.TEENG-9307
4341. Precipitation Anomalies and Trends Estimated via Satellite Rainfall Products in the Cananeia–Iguape Coastal System, Southeast Region of Brazil J. Baratto et al. https://doi.org/10.3390/cli12020022
4342. A progressive prediction model towards home-based stroke rehabilitation programs W. Bo et al. https://doi.org/10.1016/j.smhl.2021.100239
4343. Evaluation of machine learning techniques to select marine oil spill response methods under small-sized dataset conditions S. Mohammadiun et al. https://doi.org/10.1016/j.jhazmat.2022.129282
4344. LIR-Net:Learnable Iterative Reconstruction Network for Fan Beam CT Sparse-View Reconstruction Y. Cheng et al. https://doi.org/10.1109/TCI.2024.3358673
4345. TPST: A Traffic Flow Prediction Model Based on Spatial–Temporal Identity Y. Hou et al. https://doi.org/10.1002/cpe.70011
4346. Model Biokinetika Sistem Kontak Stabilisasi Lumpur Air Lindi Berdasarkan Pengaruh Fosfor dan Variasi Waktu Detensi Unit Kontak M. Kahendran et al. https://doi.org/10.14710/jil.22.1.28-42
4347. Machine learning-guided multi-site combinatorial mutagenesis enhances the thermostability of pectin lyase Z. Zhang et al. https://doi.org/10.1016/j.ijbiomac.2024.134530
4348. Evaluating land suitability for spatial planning in arid regions of eastern Iran using fuzzy logic and multi-criteria analysis M. Akbari et al. https://doi.org/10.1016/j.ecolind.2018.11.035
4349. A data generation framework for extremely rare case signals T. Chalongvorachai & K. Woraratpanya https://doi.org/10.1016/j.heliyon.2021.e07687
4350. Source apportionment and spatial distribution of potentially toxic elements in soils: A new exploration on receptor and geostatistical models Z. Wang et al. https://doi.org/10.1016/j.scitotenv.2020.143428
4351. A multi-decadal national scale assessment of reference evapotranspiration methods in continental and temperate climate zones of South Korea E. Lee et al. https://doi.org/10.1016/j.jhydrol.2023.130021
4352. Prediction of the tensile strength of a tropical wood species Terminalia superba assembled by gluing: a comparative intelligent study D. Josué et al. https://doi.org/10.1080/17486025.2024.2347283
4353. Mathematical optimization of multilinear and artificial neural network regressions for mineral composition of different tea types infusions Y. Durmus et al. https://doi.org/10.1038/s41598-024-69149-1
4354. An investigation into exhaled particle dispersion under stratum ventilation with a pulsating air supply Y. Xie et al. https://doi.org/10.1177/1420326X251336124
4355. Non-linear Interactions Driving Food Security of Smallholder Farm Households in the Western Highlands of Guatemala L. Barba-Escoto et al. https://doi.org/10.3389/fsufs.2020.00051
4356. Automated measurement of hallux valgus angles using a deep learning model: validation and comparison with surgeons of varying expertise Q. Wang et al. https://doi.org/10.1038/s41598-026-42100-2
4357. AI-driven seasonal streamflow prediction in Victoria: a focus on ENSO climate predictor S. Bani et al. https://doi.org/10.1007/s00477-026-03256-5
4358. Deep learning in the COVID-19 epidemic: A deep model for urban traffic revitalization index Z. Lv et al. https://doi.org/10.1016/j.datak.2021.101912
4359. Burial and subsequent growth of rigid ryegrass (Lolium rigidum) and ripgut brome (Bromus diandrus) following strategic deep tillage C. Borger et al. https://doi.org/10.1017/wsc.2024.11
4360. Biomarker-Informed Machine Learning Model of Cognitive Fatigue from a Heart Rate Response Perspective K. Lee et al. https://doi.org/10.3390/s21113843
4361. Machine Learning Approaches to Improve North American Precipitation Forecasts C. Sengoz et al. https://doi.org/10.1109/ACCESS.2023.3309054
4362. Comprehensive and Accurate Prediction of Band Gap for Lead-Free Double Perovskites through Self-Modified Machine Learning Strategy J. Lan et al. https://doi.org/10.1021/acs.jpcc.3c05806
4363. Comparative analysis of select techniques and metrics for data reconciliation in smart energy distribution network J. Ramasamy et al. https://doi.org/10.2166/ws.2020.314
4364. Towards a formal framework for integrated design-optimization and control of mechatronicsystems F. Rahimi https://doi.org/10.1177/00368504211037460
4365. A Comparative Analysis of Different Machine Learning Algorithms Developed with Hyperparameter Optimization in the Prediction of Student Academic Success B. Demirtürk & T. Harunoğlu https://doi.org/10.3390/app15115879
4366. Warming impact of black carbon aerosols on the direct radiative forcing over a semi-arid location, Solapur in India P. Soyam et al. https://doi.org/10.1016/j.apr.2024.102249
4367. Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia S. Ghimire et al. https://doi.org/10.1016/j.jclepro.2019.01.158
4368. Assessing the Performance of Kaiser’s Rule in Categorical Principal Component Analysis: A Comparison with Contemporary Methods for Factor Retention N. Martínez Ramos & M. Rondón Sepúlveda https://doi.org/10.1080/15366367.2025.2579488
4369. Early-Onset of Obesity Model: Impact of Early-Onset Obesity on Comorbidity Risk and Life Expectancy U. Wiedemann et al. https://doi.org/10.1159/000549499
4370. DAFT: Domain-Augmented Fine-Tuning for Large Language Models in Emotion Recognition of Health Misinformation Y. Zhao et al. https://doi.org/10.3390/app152312690
4371. A review and analysis of regression and machine learning models on commercial building electricity load forecasting B. Yildiz et al. https://doi.org/10.1016/j.rser.2017.02.023
4372. Repeated-batch fermentation of Scheffersomyces stipitis in biofilm reactor for ethanol production from the detoxified and glucose- or xylose-enriched rice husk hydrolysate and its kinetic modeling N. Ben Bader et al. https://doi.org/10.1016/j.fuel.2022.125053
4373. Brightness Temperature Image Reconstruction of the Tilted Mirrored Aperture Synthesis Using CNN and Transformer C. Xiao et al. https://doi.org/10.1109/TGRS.2024.3376577
4374. Deciphering process-morphology relationships in magnesite-derived nesquehonite crystallization using interpretable machine learning F. Weng et al. https://doi.org/10.1016/j.partic.2026.08.007
4375. Fine-grained crowd distribution forecasting with multi-order spatial interactions using mobile phone data M. Li et al. https://doi.org/10.1016/j.trc.2022.103908
4376. Adaptive Machine Learning for Automated Modeling of Residential Prosumer Agents D. Toquica et al. https://doi.org/10.3390/en13092250
4377. Prediction of Intensive Care Unit Length of Stay in the MIMIC-IV Dataset L. Hempel et al. https://doi.org/10.3390/app13126930
4378. Intelligent machining error prediction and compensation system based on convolutional neural networks and improved genetic algorithm W. Bai https://doi.org/10.1038/s41598-026-46424-x
4379. New model for confinement of reinforced concrete columns with an ultra-high strength close to 200 MPa H. Abdesselam et al. https://doi.org/10.1016/j.engstruct.2019.109594
4380. Predicting Academic Performance: Analysis of Students’ Mental Health Condition from Social Media Interactions M. Mukta et al. https://doi.org/10.3390/bs12040087
4381. Identifying the meta, para and ortho isomers in octa(aminophenyl)silsesquioxane (OAPS) from joint experimental characterizations and theoretical predictions of the IR and NMR spectra S. Salimi et al. https://doi.org/10.1016/j.molstruc.2022.133510
4382. UAV Inspection and Collision-Aware Visual Perception Using Topology-Preserving RGB–Infrared Power-Line Graph Reconstruction J. He et al. https://doi.org/10.3390/electronics15204669
4383. Air pollution and atmospheric variables in Türkiye: A comprehensive analysis S. Ciarlantini et al. https://doi.org/10.1016/j.apr.2025.102826
4384. Evaluation of precipitation products over different climatic zones of Pakistan M. Khan et al. https://doi.org/10.1007/s00704-022-04355-3
4385. Predictive modeling of milk adulteration with urea content using the gray wolf optimization algorithm and long and short-term memory network model W. Zhang et al. https://doi.org/10.1080/00387010.2024.2331616
4386. Climatic-to-vegetation transition in controlling the ratio of transpiration to evapotranspiration in China revealed by multi-dataset fusion Q. Zhao et al. https://doi.org/10.1016/j.agrformet.2026.111431
4387. Theoretical and experimental investigation on the thermal penetration depth in the surrounding rock of a deeply buried high-temperature tunnel J. Che et al. https://doi.org/10.1016/j.ijthermalsci.2023.108876
4388. Comparative benchmark of machine learning models for predicting perovskite solar cell performance Y. Velez-Galvis et al. https://doi.org/10.1016/j.solener.2026.114959
4389. Modelling of the adsorption of urea herbicides by tropical soils with an Adaptive‐Neural‐based Fuzzy Inference System B. Agbaogun et al. https://doi.org/10.1002/cem.3335
4390. Towards sustainable short-form video: Modelling solutions for social and environmental challenges G. Szalkowski et al. https://doi.org/10.12688/f1000research.161812.1
4391. Evaluation of Gridded Precipitation Data Products for Hydrological Applications in Complex Topography D. Gampe & R. Ludwig https://doi.org/10.3390/hydrology4040053
4392. Deep learning-assisted prediction of viscoplastic flow in superhydrophobic channels A. Joulaei et al. https://doi.org/10.1063/5.0268110
4393. Consensus holistic virtual screening for drug discovery: a novel machine learning model approach S. Moshawih et al. https://doi.org/10.1186/s13321-024-00855-8
4394. Building Agent-Based Decision Support Systems for Word-of-Mouth Programs: A Freemium Application M. Chica & W. Rand https://doi.org/10.1509/jmr.15.0443
4395. Application of cross validation approaches to examine soft computing systems for forecasting soil liquefaction M. Rahman & M. Sayed https://doi.org/10.1016/j.bdes.2025.100038
4396. An empirical comparison of generalized structured component analysis and partial least squares path modeling under variance-based structural equation models G. Cho & J. Choi https://doi.org/10.1007/s41237-019-00098-0
4397. Construction of a personality trait prediction model based on color perception preference and personalized cognitive intervention pathways in art education S. Yang et al. https://doi.org/10.3389/fpsyg.2026.1876102
4398. BMC-FedStack: Secure and robust federated stacking for residential short-term load forecasting G. Han et al. https://doi.org/10.1016/j.enbuild.2026.117896
4399. Predicting junglerice (Echinochloa colona L.) emergence as a function of thermal time in the humid pampas of Argentina G. Picapietra et al. https://doi.org/10.1080/09670874.2020.1778811
4400. A Wind Speed Forecasting Method Based on Machine Learning for Operating Unguided Submunitions from a Cluster Munition S. Lee et al. https://doi.org/10.1007/s42405-024-00751-3
4401. Transitive reasoning: A high-performance computing model for significant pattern discovery in cognitive IoT sensor network V. Jha & P. Tripathi https://doi.org/10.1016/j.adhoc.2024.103700
4402. Comparative Evaluation of Deep Learning Architectures for Electricity Demand Forecasting T. Aravanis & A. Kanavos https://doi.org/10.3390/math14050827
4403. Adaptive thresholding for CT metal artifact reduction via LangGraph Y. Kim et al. https://doi.org/10.1088/1361-6560/ae7ec4
4404. The Role of Hydrological Signatures in Calibration of Conceptual Hydrological Model E. Melišová et al. https://doi.org/10.3390/w12123401
4405. Defect Enhancement and Image Noise Reduction Analysis Using Partial Least Square-Generative Adversarial Networks (PLS-GANs) in Thermographic Nondestructive Evaluation Q. Fang et al. https://doi.org/10.1007/s10921-021-00827-0
4406. Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations A. Samantaray et al. https://doi.org/10.5194/gmd-17-3321-2024
4407. Forecasting annual energy consumption using machine learnings: Case of Indonesia R. Kurniawan & S. Managi https://doi.org/10.1088/1755-1315/257/1/012032
4408. Observed trends and future projections of seasonal rainfall onset, cessation, length, and rainy days in Rwanda N. Sebaziga et al. https://doi.org/10.1007/s44292-026-00084-8
4409. Physics-guided unmixing of spaceborne hyperspectral data for effective photovoltaic area estimation S. He et al. https://doi.org/10.1016/j.aei.2026.104970
4410. Evaluation of Anti-wear Properties of Different Vegetable Oils Based on QSPR Model J. Liu et al. https://doi.org/10.1007/s11249-023-01704-9
4411. Lake Water-Level fluctuations forecasting using Minimax Probability Machine Regression, Relevance Vector Machine, Gaussian Process Regression, and Extreme Learning Machine H. Bonakdari et al. https://doi.org/10.1007/s11269-019-02346-0
4412. Performance analysis of machine learning-based prediction models for residential building construction waste A. Gulghane et al. https://doi.org/10.1007/s42107-023-00708-z
4413. Applicability Assessment of GFED4 and GFED5 on Forest Fires in Chinese Mainland and Its Fire-Scale Patterns Change X. Wang et al. https://doi.org/10.3390/rs17203461
4414. Nowcasting thunderstorm hazards using machine learning: the impact of data sources on performance J. Leinonen et al. https://doi.org/10.5194/nhess-22-577-2022
4415. Acoustic Characterization and Modeling of Silicone-Bonded Cocoa Crop Waste Using a Model Based on the Gaussian Support Vector Machine V. Puyana-Romero et al. https://doi.org/10.3390/fib10030025
4416. A fast and robust mixture gases identification and concentration detection algorithm based on attention mechanism equipped recurrent neural network with double loss function X. Pan et al. https://doi.org/10.1016/j.snb.2021.129982
4417. Assessment of spatial monitoring of geological carbon storage using InSAR Y. Li et al. https://doi.org/10.1016/j.jgsce.2025.205591
4418. A Hierarchical Sparsity Unmixing Method to Address Endmember Variability in Hyperspectral Image J. Zou et al. https://doi.org/10.3390/rs10050738
4419. Graph neural networks for computational plasma physics on unstructured grids: application to approximate the Poisson equation for Hall-Effect Thrusters modeling G. Vigot et al. https://doi.org/10.1007/s44205-025-00146-w
4420. Optimal Dependence of Performance and Efficiency of Collaborative Filtering on Random Stratified Subsampling S. Poudel & M. Bikdash https://doi.org/10.26599/BDMA.2021.9020032
4421. Machine Learning for Projecting Extreme Precipitation Intensity for Short Durations in a Changing Climate H. Hu & B. Ayyub https://doi.org/10.3390/geosciences9050209
4422. Development and optimization of geotechnical soil maps using various geostatistical and spatial interpolation techniques: a comprehensive study Z. Ijaz et al. https://doi.org/10.1007/s10064-023-03244-x
4423. Method for calculating porosity in tight sandstone reservoir thin sections based on ICSO intelligent algorithm T. Liu et al. https://doi.org/10.1016/j.uncres.2025.100147
4424. Structure-based machine learning model for discovering pregnane X receptor (PXR) agonists and biological activity validation F. Huang et al. https://doi.org/10.1007/s00204-026-04447-3
4425. 3D photogrammetry improves measurement of growth and biodiversity patterns in branching corals J. Curtis et al. https://doi.org/10.1007/s00338-023-02367-7
4426. Research on deep learning-based missing echo restoration method for weather radar mosaic data H. Guo et al. https://doi.org/10.5194/amt-19-6341-2026
4427. Development and validation of a model for predicting fire behaviour in spinifex grasslands of arid Australia N. Burrows et al. https://doi.org/10.1071/WF17155
4428. Runoff Estimation Using Advanced Soft Computing Techniques: A Case Study of Mangla Watershed Pakistan U. Humphries et al. https://doi.org/10.3390/w14203286
4429. Toward intelligent construction: Prediction of mechanical properties of manufactured-sand concrete using tree-based models J. Zhang et al. https://doi.org/10.1016/j.jclepro.2020.120665
4430. A Semantic and Syntactic Enhanced Neuromorphic Computing System and Its Application in Consumer Sentiment Analysis X. Ji et al. https://doi.org/10.1109/TCE.2024.3442882
4431. Resistance Analysis of Morphologies in Headwater Mountain Streams S. Cedillo et al. https://doi.org/10.3390/w13162207
4432. KE-STCN: An adaptive multi-scale traffic flow prediction method based on knowledge graph J. Cao et al. https://doi.org/10.1016/j.neucom.2025.131771
4433. Predicting climate change using an autoregressive long short-term memory model S. Chin & V. Lloyd https://doi.org/10.3389/fenvs.2024.1301343
4434. Uso de redes neuronales LSTM y ConvLSTM para el pronóstico de precipitación diaria en Puno, Perú (2016-2022) J. Rojas et al. https://doi.org/10.46932/sfjdv7n6-036
4435. Effects of variability in experimental database on machine-learning-based prediction of ultimate load of circular concrete-filled steel tubes N. Ho & T. Le https://doi.org/10.1016/j.measurement.2021.109198
4436. The Big Data Paradox in Clinical Practice P. Msaouel https://doi.org/10.1080/07357907.2022.2084621
4437. Hybrid Wavelet-SVR, machine learning, and deep learning models for predicting clean energy markets amidst global events İ. Kayral et al. https://doi.org/10.1007/s00521-025-11345-9
4438. Predicting the dietary fiber content of fresh-cut bamboo shoots using a visible and near-infrared hyperspectral technique X. Xu et al. https://doi.org/10.1007/s11694-023-01845-4
4439. Performance of Screened-Exchange Functionals for Band Gaps and Lattice Constants of Crystals C. Zhang et al. https://doi.org/10.1021/acs.jctc.2c00822
4440. Neck Muscle EMG-Force Relationship and Its Reliability During Isometric Contractions R. Lo Martire et al. https://doi.org/10.1186/s40798-017-0083-2
4441. Selection of automatic short answer grading techniques using contextual bandits for different evaluation measures S. Roy et al. https://doi.org/10.1007/s12572-017-0202-9
4442. Lake water level modeling using newly developed hybrid data intelligence model Z. Yaseen et al. https://doi.org/10.1007/s00704-020-03263-8
4443. Swell-dominated wave parameter retrieval from oblique coastal video under variable camera geometry T. Ngene et al. https://doi.org/10.1016/j.apor.2026.105161
4444. Artificial Neural Network Model to relate Organization Characteristics and Construction Project Delivery Methods U. Gazder et al. https://doi.org/10.1016/j.procs.2018.07.144
4445. OTIMIZAÇÃO DA BIOPROSPECÇÃO DE ATIVOS BIOLÓGICOS POR INTELIGÊNCIA ARTIFICIAL W. Kume & J. Costa https://doi.org/10.56238/revgeov17n4-029
4446. Estimating Daily Global Evapotranspiration Using Penman–Monteith Equation and Remotely Sensed Land Surface Temperature R. Raoufi & E. Beighley https://doi.org/10.3390/rs9111138
4447. Temporal forecasting by converting stochastic behaviour into a stable pattern in electric grid A. Qashou et al. https://doi.org/10.1007/s13198-024-02454-0
4448. Wavelet-Enhanced Transformer for Adaptive Multi-Period Time Series Forecasting P. Yu et al. https://doi.org/10.3390/app152312698
4449. Measuring Latent Trust Patterns in Large Language Models in the Context of Human-AI Teaming D. Koehl & L. Vangsness https://doi.org/10.1177/21695067231192869
4450. Seasonal contributions and efficiency analysis of green-gray-blue coupled infrastructures system for the improvement of water quality in urban lakes Z. Guo et al. https://doi.org/10.1016/j.jenvman.2025.125379
4451. Sensitivity analysis-based data snooping for general symmetric transformation of 3-D point sets B. Wang et al. https://doi.org/10.1016/j.measurement.2026.120886
4452. Assessing the performance of multivariate data analysis for predicting solar radiation using alternative meteorological variables M. Özbuldu & Y. Şekerli https://doi.org/10.51753/flsrt.1590684
4453. A model for the assessment of bluetongue virus serotype 1 persistence in Spain C. Aguilar-Vega et al. https://doi.org/10.1371/journal.pone.0232534
4454. Estimating crop biomass using leaf area index derived from Landsat 8 and Sentinel-2 data T. Dong et al. https://doi.org/10.1016/j.isprsjprs.2020.08.003
4455. 3.5 GHz Outdoor Radio Signal Strength Prediction With Machine Learning Based on Low-Cost Geographic Features Y. Liu et al. https://doi.org/10.1109/TAP.2022.3175214
4456. Identifikasi Kedalaman Pirit dan Kaitannya Terhadap Kesehatan dan Produktivitas Tanaman Kelapa Sawit (Elaeis guineensis Jacq.) ( Studi Kasus di Perkebunan PT Sawit Sumbermas Sarana Tbk ) A. Primayuda https://doi.org/10.29244/jitl.24.1.6-13
4457. Evaluation and spatial downscaling of CRU TS precipitation data in the Philippines A. Salvacion et al. https://doi.org/10.1007/s40808-018-0477-2
4458. Predicting water level fluctuations in glacier-fed lakes by ensembling individual models into a quad-meta model S. Shah et al. https://doi.org/10.1080/19942060.2024.2449124
4459. Neural network approach for efficient calculation of the current correction value in the femtoampere range for a new generation of ionizing radiation monitors at CERN J. Szumega et al. https://doi.org/10.1016/j.radphyschem.2021.109539
4460. Intention Prediction of a Hypersonic Glide Vehicle Using a Satellite Constellation Based on Deep Learning Y. Cheng et al. https://doi.org/10.3390/math10203754
4461. A multi-output deep learning model for energy demand and port availability forecasting in EV charging infrastructure S. Makaremi https://doi.org/10.1016/j.energy.2025.134582
4462. Interpretable machine learning for elucidating electrosorption mechanisms and optimizing heavy metal removal in capacitive deionization C. Dai et al. https://doi.org/10.1016/j.jece.2026.124832
4463. Advancing air pollution forecasting: a review of physical, statistical, and machine learning methods A. Rawat et al. https://doi.org/10.1007/s11356-026-37789-7
4464. Predictive modeling for savonius hydrokinetic turbine performance: a machine learning investigation M. Khojasteh et al. https://doi.org/10.1016/j.energy.2025.139109
4465. Spatiotemporal Data-Driven Hourly Bike-Sharing Demand Prediction Using ApexBoost Regression M. Biswas et al. https://doi.org/10.1007/s41060-025-00820-0
4466. Predicting Heavy Metal Concentrations in Shallow Aquifer Systems Based on Low-Cost Physiochemical Parameters Using Machine Learning Techniques T. Huynh et al. https://doi.org/10.3390/ijerph191912180
4467. An Anchor Point–Assisted Image-Matching Method for Weakly Textured Scenes Using Structured Features M. Chen et al. https://doi.org/10.14358/PERS.26-00014R2
4468. Comparative Analysis of Deep Learning and Decision Tree Approaches for Predicting Aircraft Engine Remaining Useful Life H. Madjour et al. https://doi.org/10.2478/fas-2023-0012
4469. Forecast Skill of Minimum and Maximum Temperatures on Subseasonal‐to‐Seasonal Timescales Over South Africa S. Phakula et al. https://doi.org/10.1029/2019EA000697
4470. Integrating Large Wood Jams into Hydraulic Models: Evaluating a Porous Plate Modeling Method R. Ventres‐Pake et al. https://doi.org/10.1111/1752-1688.12818
4471. Machine learning techniques for soil moisture prediction in arid and semi-arid regions: A case study of Morocco A. Elmotawakkil et al. https://doi.org/10.1016/j.ige.2025.11.001
4472. Feature based remote sensing image registration techniques: a comprehensive and comparative review I. Misra et al. https://doi.org/10.1080/01431161.2022.2114112
4473. Uncertainty Quantification of Radiation Pattern in Radome-Enclosed Antennas via Integrated Gaussian Process Regression and Grey Wolf Optimization Z. Zhang et al. https://doi.org/10.1109/LAWP.2025.3569433
4474. In-DMU: Modeling Uncertainty in Interferometric SAR-Based Deformation Monitoring T. Wang et al. https://doi.org/10.1109/TGRS.2025.3595272
4475. Prediction of surface urban heat island based on predicted consequences of urban sprawl using deep learning: A way forward for a sustainable environment S. Fu et al. https://doi.org/10.1016/j.pce.2024.103682
4476. Predicting Software Cohesion Metrics with Machine Learning Techniques E. Haner Kırğıl & T. Erçelebi Ayyıldız https://doi.org/10.3390/app13063722
4477. Analysis on the effect of salinity in underwater wireless optical communication S. Kumar et al. https://doi.org/10.1080/1064119X.2019.1569739
4478. Research on Price Prediction of Construction Materials Based on VMD-SSA-LSTM S. Xiong et al. https://doi.org/10.3390/app15042005
4479. Development of machine learning-based shelf-life prediction models for multiple marine fish species and construction of a real-time prediction platform F. Cui et al. https://doi.org/10.1016/j.foodchem.2024.139230
4480. Intelligent consensus predictions of bioconcentration factor of pharmaceuticals using 2D and fragment-based descriptors K. Khan et al. https://doi.org/10.1016/j.envint.2022.107625
4481. Disaggregable Outage-Aware SNR Modeling Under PDL Uncertainty for Optical Network Digital Twins E. Miotto et al. https://doi.org/10.1109/OJCOMS.2026.3741461
4482. 2D SPARSE INVERSION GRAVITY METHOD FOR SUBSURFACE INTERPRETATION BY SIMPEG: A CASE STUDY OF UNGARAN VOLCANO A. Setyawan et al. https://doi.org/10.35741/issn.0258-2724.59.3.36
4483. Spatial Extreme Value Modeling of Seawater Wave Height in Banyuwangi with Smith and Geometric Gaussian Models A. Azzahra et al. https://doi.org/10.4274/jems.2026.33154
4484. Ethanol production from acid-pretreated and detoxified rice straw as sole renewable resource M. Germec & I. Turhan https://doi.org/10.1007/s13399-018-0310-1
4485. Predictive applications of Australian flood loss models after a temporal and spatial transfer R. Hasanzadeh Nafari & T. Ngo https://doi.org/10.1080/19475705.2018.1445666
4486. Error Correction of Meteorological Data Obtained with Mini-AWSs Based on Machine Learning J. Ha et al. https://doi.org/10.1155/2018/7210137
4487. Biomass Estimation of Apple and Citrus Trees Using Terrestrial Laser Scanning and Drone-Mounted RGB Sensor M. Lee et al. https://doi.org/10.3390/rs17152554
4488. Integration hierarchical analysis process (AHP) and geographic information systems to map flood risk levels in the province of Utcubamba, Peru C. Rivera et al. https://doi.org/10.3389/fenvs.2026.1935148
4489. A predictive model to estimate effort in a sprint using machine learning techniques M. Ramessur & S. Nagowah https://doi.org/10.1007/s41870-021-00669-z
4490. Forecasting commencing enrolments under data sparsity: a zero-shot time series foundation models framework for higher education planning J. Jetwiriyanon et al. https://doi.org/10.1080/29966892.2026.2718692
4491. Hybrid transformer model for wind power generation forecasting K. Altun et al. https://doi.org/10.1007/s12046-026-03222-5
4492. Predicting the leachate generation from wet phosphogypsum stack using a water-balance-analysis based model M. Meng et al. https://doi.org/10.1016/j.envres.2022.113338
4493. Using Machine Learning for Estimating Rice Chlorophyll Content from In Situ Hyperspectral Data G. An et al. https://doi.org/10.3390/rs12183104
4494. Robot-Driven Calibration and Accuracy Assessment of Meta Quest 3 Inside-Out Tracking Using a TECHMAN TM5-900 Collaborative Robot J. Lopez-Xarbau et al. https://doi.org/10.3390/s26082285
4495. A hybrid homotopy analysis method with artificial neural network for MHD Jeffery–Hamel slip flow A. Khudhur & A. Jasim https://doi.org/10.1016/j.physleta.2026.132104
4496. Applying Hybrid Lstm-Gru Model Based on Heterogeneous Data Sources for Traffic Speed Prediction in Urban Areas N. Zafar et al. https://doi.org/10.3390/s22093348
4497. Machine Learning Models and Mathematical Approaches for Predictive IoT Smart Parking V. Knights et al. https://doi.org/10.3390/s25072065
4498. Statistical modeling of the assembly of single-layer domes E. Lebed et al. https://doi.org/10.1051/e3sconf/20199704004
4499. Spatiotemporal Assessment and Correction of Gridded Precipitation Products in North Western Morocco L. Ait Dhmane et al. https://doi.org/10.3390/atmos14081239
4500. How well can ChatGPT forecast tourism demand? D. Wu et al. https://doi.org/10.1016/j.tourman.2024.105119
4501. Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing J. Qi et al. https://doi.org/10.1109/TASLP.2022.3231714
4502. Machine learning-based forecasting of relativistic electron fluences at GEO three days in advance using data from the 24th solar cycle C. Azra-Gorskaya et al. https://doi.org/10.1016/j.asr.2026.10.037
4503. A quantum mechanics-based framework for infectious disease modeling W. He et al. https://doi.org/10.1038/s41598-025-96817-7
4504. Employee acceptance of AI-driven performance management systems in hospitality L. Yu et al. https://doi.org/10.1016/j.techsoc.2026.103585
4505. Construction of an Integrated Drought Monitoring Model Based on Deep Learning Algorithms Y. Zhang et al. https://doi.org/10.3390/rs15030667
4506. Mapping the Continuous Cover of Invasive Noxious Weed Species Using Sentinel-2 Imagery and a Novel Convolutional Neural Regression Network F. Xing et al. https://doi.org/10.3390/rs16091648
4507. Sustainable development goal 3: is Ghana on track with neonatal mortality? Z. Adama et al. https://doi.org/10.1186/s12889-025-25461-7
4508. Probabilistic slope stability analysis using subset simulation enhanced by ensemble machine learning techniques F. Ahmad et al. https://doi.org/10.1007/s40808-023-01882-4
4509. What Is the Potential of Integrating Phase Space Reconstruction with SVM-FFA Data-Intelligence Model? Application of Rainfall Forecasting over Regional Scale H. Tao et al. https://doi.org/10.1007/s11269-018-2028-z
4510. Soft-Computing Techniques for Predicting Seismic Bearing Capacity of Strip Footings in Slopes D. Kumar et al. https://doi.org/10.3390/buildings13061371
4511. Real-Time ITO Layer Thickness for Solar Cells Using Deep Learning and Optical Interference Phenomena X. Fan et al. https://doi.org/10.3390/en16166049
4512. Prediction of Global Horizontal Irradiance Using an Explainable Data Driven Machine Learning Algorithms R. Gupta et al. https://doi.org/10.1080/15325008.2024.2310771
4513. Model evaluation using ballistic trajectories and preliminary mesoscale model accuracies with age of global model initialization data J. Cogan https://doi.org/10.1002/met.1684
4514. Performance predictors for graphics processing units applied to dark‐silicon‐aware design space exploration R. Sonohata et al. https://doi.org/10.1002/cpe.6877
4515. Daily evapotranspiration estimation in Germany through multi-source data fusion and hybrid machine learning models S. Ahmadpour et al. https://doi.org/10.1080/01431161.2026.2716391
4516. Investigation of the effectiveness of top-down natural ventilation of a poultry building in a hot-summer mediterranean climate M. Fezai et al. https://doi.org/10.1177/01436244231215454
4517. Estimating the carbon content of oceans using satellite sensor data A. Sooknanan & P. Hosein https://doi.org/10.1186/s40537-022-00647-7
4518. Geostatistical Analysis for delineating sterile inclusions in Sidi Chennane' phosphatic series, Morrocco K. Baba et al. https://doi.org/10.15446/esrj.v18n2.41173
4519. Predicting Gasoline Vehicle Fuel Consumption in Energy and Environmental Impact Based on Machine Learning and Multidimensional Big Data Y. Yang et al. https://doi.org/10.3390/en15051602
4520. An accuracy-level method for robust evaluation in predictive analytics M. Agustini et al. https://doi.org/10.1016/j.dajour.2025.100661
4521. Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives E. Hasan et al. https://doi.org/10.1145/3742421
4522. Efficient boundary conditions identification in thermal simulation of the spindle system with reduced order model and differential evolution algorithm F. Tan et al. https://doi.org/10.1016/j.csite.2024.104526
4523. Numerical Analysis of the Submerged Horizontal Plate Device Subjected to Representative Regular and Realistic Irregular Waves of a Sea State G. Thum et al. https://doi.org/10.3390/fluids9080188
4524. Repeatability of force signals in aerial circus straps M. Cossin et al. https://doi.org/10.1177/1754337117732901
4525. Predicting global warming potential: A self-training and ensemble machine learning approach S. Park et al. https://doi.org/10.1116/6.0004715
4526. Characterizing drought prediction with deep learning: A literature review A. Márquez-Grajales et al. https://doi.org/10.1016/j.mex.2024.102800
4527. Comparative study on the correlation between human local and overall thermal sensations based on supervised machine learning H. Zhao et al. https://doi.org/10.1016/j.enbuild.2024.115061
4528. Recursive multivariate principal‐monotonicity inferential climate downscaling G. Cheng et al. https://doi.org/10.1002/qj.3126
4529. Analysis of Landsat-8 OLI Imagery for Estimating Exposed Bedrock Fractions in Typical Karst Regions of Southwest China Using a Karst Bare-Rock Index J. Pei et al. https://doi.org/10.3390/rs10091321
4530. Limitations Posed by Free DEMs in Watershed Studies: The Case of River Tanaro in Italy R. Tavares da Costa et al. https://doi.org/10.3389/feart.2019.00141
4531. An investigation of the thermal behavior of constructal theory-based pore-scale porous media by using a combination of computational fluid dynamics and machine learning M. Mesgarpour et al. https://doi.org/10.1016/j.ijheatmasstransfer.2022.123072
4532. Optimizing the flow adjustment of constituent concentrations via LOESS for trend analysis Z. Simpson & B. Haggard https://doi.org/10.1007/s10661-018-6461-5
4533. Clay Nanosize Effects on the Rheological Behavior at Various Elevated Temperatures and Mechanical Properties of the Cement Paste: Experimental and Modeling A. Mohammed et al. https://doi.org/10.1007/s40996-021-00604-z
4534. Geometric Algebra Multi-Order Graph Neural Network for Traffic Prediction D. Zang et al. https://doi.org/10.1109/TBDATA.2024.3442533
4535. Handling uncertainty in eHealth sensors using fuzzy system modeling A. Gupta & N. Mukherjee https://doi.org/10.1007/s12553-020-00465-y
4536. An implementation of XGBoost algorithm to estimate effective porosity on well log data M. Fajrul Haqqi et al. https://doi.org/10.1088/1742-6596/2498/1/012011
4537. Thermal dispersion model of cooling water discharges from industrial activities of steam power plants (PLTU) on the north coast of Paiton, East Java M. Fikri et al. https://doi.org/10.1088/1755-1315/429/1/012022
4538. Simulation model of vegetation dynamics by combining static and dynamic data using the gated recurrent unit neural network-based method P. Zhang et al. https://doi.org/10.1016/j.jag.2022.102901
4539. Machine learning techniques for emotion detection and sentiment analysis: current state, challenges, and future directions A. Alslaity & R. Orji https://doi.org/10.1080/0144929X.2022.2156387
4540. Satellite-derived daily shortwave radiation over the Tibetan Plateau considering topographic effects: Method and products Y. Xian et al. https://doi.org/10.1016/j.rse.2026.115547
4541. Predicting lecithin concentration from differential mobility spectrometry measurements with linear regression models and neural networks A. Anttalainen et al. https://doi.org/10.1016/j.talanta.2020.121926
4542. Simultaneous trajectory tracking and aerial manipulation using a multi-stage model predictive control S. Emami & A. Banazadeh https://doi.org/10.1016/j.ast.2021.106573
4543. Assessment of Satellite and Reanalysis Precipitation Data Using Statistical and Wavelet Analysis in Semi-Arid, Morocco A. Chakri et al. https://doi.org/10.3390/w17111714
4544. Developing broadband spectral index for estimating crop canopy water content X. Huang et al. https://doi.org/10.1016/j.jag.2026.105637
4545. Forecasting air quality time series using deep learning B. Freeman et al. https://doi.org/10.1080/10962247.2018.1459956
4546. NDVI‐based estimates of evapotranspiration of winter wheat indicate positive effects of N fertilizer application on agronomic water‐use efficiency P. Drerup et al. https://doi.org/10.1111/jac.12364
4547. Machine learning approaches to predict oxidative potential of fine particulate matter based on chemical constituents J. Lee et al. https://doi.org/10.1016/j.engappai.2025.111170
4548. Wind Turbine Blade Material Behavior in Abrasive Wear Conditions C. Muntenita et al. https://doi.org/10.3390/polym16243483
4549. HilalPy: Software to analyse lunar sighting criteria M. Faid et al. https://doi.org/10.1016/j.simpa.2023.100593
4550. Monthly Precipitation Patterns in a Region Vulnerable to Climate-Related Hazards—A Case Study from Poland W. Kasperska-Wołowicz et al. https://doi.org/10.3390/w8090362
4551. Un estudio de viabilidad y un marco metodológico que aplica modelos de aprendizaje automático en el nexo Agua – Energía – Alimentos en Galápagos: Oportunidades y desafíos ante la escasez de datos M. Jiménez Copa & Y. Fernández Fernández https://doi.org/10.69639/arandu.v12i4.1835
4552. Enhancing the Efficiency of Confrontation Naming Assessment for Aphasia Using Computer Adaptive Testing G. Fergadiotis et al. https://doi.org/10.1044/2018_JSLHR-L-18-0344
4553. A CEEMDAN-GNN-transformer hybrid model for air quality index forecasting: a case study of Chang’an town, Dongguan, China S. He et al. https://doi.org/10.3389/fenvs.2025.1653446
4554. Leaf area index-based phenotypic assessment of sweet potato varieties using UAV multispectral imagery and a hybrid retrieval approach P. Tsele et al. https://doi.org/10.1016/j.atech.2025.100960
4555. Synergistic interfacial engineering of mesoporous magnetic metal oxide TiO2 nanocomposites for sustainable visible-light photocatalysis: Experimental insights and ML-based performance prediction S. Kazmi et al. https://doi.org/10.1371/journal.pone.0348881
4556. Dynamic prediction of mechanized shield tunneling performance R. Wang et al. https://doi.org/10.1016/j.autcon.2021.103958
4557. Near real-time wind speed forecast model with bidirectional LSTM networks L. Joseph et al. https://doi.org/10.1016/j.renene.2022.12.123
4558. How large was the daily hunting range of prehistoric high-altitude populations in hypoxic environments? — evidence from 87Sr/86Sr, δ13C, and δ18O analyses of archaeological animal teeth W. Cheng et al. https://doi.org/10.1016/j.jas.2026.106707
4559. Hormesis and hydra effects revealed by intraspecific overcompensation models and dose–response curves S. Tang et al. https://doi.org/10.1098/rsif.2025.0169
4560. Long-wave Infrared polarization characteristics of airport runways target in hazy based on the PG-BM model G. Gao et al. https://doi.org/10.1364/OE.581800
4561. Considering the self-adaptive segmentation of time series in interval prediction of remaining useful life for lithium-ion battery X. Pang et al. https://doi.org/10.1016/j.est.2023.107862
4562. Improvement of metal artifact reduction in dental CBCT using a CdTe photon-counting detector: Simulation study S. Lee et al. https://doi.org/10.1016/j.nima.2024.169221
4563. Comparative Performance of Machine Learning Algorithms in the Prediction of Indoor Daylight Illuminances J. Ngarambe et al. https://doi.org/10.3390/su12114471
4564. Monitoring the kappa number of bleached pulps based on FT-Raman spectroscopy W. Gao et al. https://doi.org/10.1007/s10570-021-04333-4
4565. Prediction of body fat percentage using a new hybrid intelligent feature selection: ANN-KGA & ANN-IKGA T. Yousefi & Ö. Varlıklar https://doi.org/10.7717/peerj-cs.3984
4566. Identification potential sources of marine debris based on backward trajectory modelling in Tidung Island M. Dwianto et al. https://doi.org/10.1051/bioconf/202622006011
4567. Comparison of adaptive optical scanning holography based on new evaluation methods J. Duan et al. https://doi.org/10.1038/s41598-023-46851-0
4568. The Spatial neural network model with disruptive technology for property appraisal in real estate industry R. Lin et al. https://doi.org/10.1016/j.techfore.2021.121067
4569. Machine learning-guided prioritization of high-activity and thermostable xylanase mutants Z. Li et al. https://doi.org/10.1016/j.bidere.2026.100112
4570. HypeAIR: A novel framework for real-time low-cost sensor calibration for air quality monitoring in smart cities C. Bachechi et al. https://doi.org/10.1016/j.ecoinf.2024.102568
4571. TES-CVIDS: A Transmission Efficient Sub-Map Based Collaborative Dense VI-SLAM Framework T. Zhang et al. https://doi.org/10.1109/TIV.2024.3385452
4572. Online measurements of material flow compositions using acoustic emission: Case of gypsum and anhydrite D. Gürsel et al. https://doi.org/10.1016/j.mineng.2021.107131
4573. Comparison of Radiosonde Measurements of Meteorological Variables with Drone, Satellite Products, and WRF Simulations in the Tropical Andes: The Case of Quito, Ecuador L. Muñoz et al. https://doi.org/10.3390/atmos14020264
4574. Aquatic toxicity prediction of diverse pesticides on two algal species using QSTR modeling approach P. Banjare et al. https://doi.org/10.1007/s11356-022-22635-3
4575. System-level performance prognosis based on data augmentation for air brake systems of in-service trains J. Ding & J. Zuo https://doi.org/10.1177/16878132231215187
4576. Integration of Gaussian process regression and K means clustering for enhanced short term rainfall runoff modeling O. Kisi et al. https://doi.org/10.1038/s41598-025-91339-8
4577. Hybrid retrieval of grass biophysical variables based-on radiative transfer, active learning and regression methods using Sentinel-2 data in Marakele National Park P. Tsele & A. Ramoelo https://doi.org/10.1080/10106049.2024.2387087
4578. Retroductive reasoning: a data-driven intelligent method for knowledge discovery using cognitive IoT V. Jha & P. Tripathi https://doi.org/10.1007/s10115-025-02649-2
4579. A Numerical Study on Travel Time Based Hydraulic Tomography Using the SIRT Algorithm with Cimmino Iteration P. Qiu et al. https://doi.org/10.3390/w11050909
4580. Evaluation of CMIP6 model performance and extreme precipitation prediction in the Awash basin C. Sime & W. Dibaba https://doi.org/10.1016/j.heliyon.2023.e21578
4581. Crop weed separation through image-level segmentation: an ensemble of modified U-Net and encoder–decoder S. Ganapathy & S. Srinivasan https://doi.org/10.1007/s00521-025-11123-7
4582. Prediction of Hardness and Fracture Toughness in High-Entropy Alloy Bonded Cemented Carbides through Machine Learning C. Fan et al. https://doi.org/10.1007/s11665-025-11681-w
4583. Development of a Machine Learning-Based Model to Predict Timed-Up-and-Go Test in Older Adults M. Kraus et al. https://doi.org/10.3390/geriatrics8050099
4584. Multivariate time series energy forecasting using a hybrid neural-SVM ensemble model: A data-driven approach for energy management in Bangladesh M. Mahin et al. https://doi.org/10.1016/j.nexus.2026.100641
4585. Indirect methods of tree biomass estimation and their uncertainties M. Njana https://doi.org/10.2989/20702620.2016.1233753
4586. Validation of simplified centre of mass models during gait in individuals with chronic stroke A. Huntley et al. https://doi.org/10.1016/j.clinbiomech.2017.07.015
4587. Information Diffusion Predictive Model Using Radiation Transfer L. Alsuwaidan & M. Ykhlef https://doi.org/10.1109/ACCESS.2017.2764001
4588. Beyond R2: The Role of Polynomial Degree in Modeling External Temperature and Its Impact on Heat-Pump Energy Demand M. Masiukiewicz et al. https://doi.org/10.3390/en18205547
4589. Modelling of municipal solid waste gasification using an optimised ensemble soft computing model N. Kardani et al. https://doi.org/10.1016/j.fuel.2020.119903
4590. Evaluation and Modelling of Reference Evapotranspiration Using Different Machine Learning Techniques for a Brazilian Tropical Savanna T. Spontoni et al. https://doi.org/10.3390/agronomy13082056
4591. Smartphone-Assisted Nanozyme Colorimetric Sensor Array Combined “Image Segmentation-Feature Extraction” Deep Learning for Detecting Unsaturated Fatty Acids X. Zhong et al. https://doi.org/10.1021/acssensors.4c01142
4592. A New Approach to Purchasing Power: Discounted Gross Domestic Product Per Capita C. Gerede https://doi.org/10.24988/ije.1624210
4593. Measuring performance of low impact development practices for the surface runoff management W. Yang et al. https://doi.org/10.1016/j.ese.2020.100010
4594. Metaverse and Healthcare: Machine Learning-Enabled Digital Twins of Cancer O. Moztarzadeh et al. https://doi.org/10.3390/bioengineering10040455
4595. ETH analysis and predictions utilizing deep learning T. Zoumpekas et al. https://doi.org/10.1016/j.eswa.2020.113866
4596. A data driven approach to model thermal boundary resistance from molecular dynamics simulations A. Anandakrishnan & S. Sathian https://doi.org/10.1039/D2CP04551F
4597. Improving the Hurricane Outage Prediction Model by including tree species D. D'Amico et al. https://doi.org/10.1016/j.crm.2019.100193
4598. An Adaptive Early Warning Method for Wind Power Prediction Error L. Zhang et al. https://doi.org/10.3390/pr13123941
4599. Predicting ceramic tile quality using LSTM and CatBoost: a case study of industrial roller kiln operations M. Heydari et al. https://doi.org/10.1515/cppm-2026-0009
4600. An investigation of the impacts of a successful COVID-19 response and meteorology on air quality in New Zealand N. Talbot et al. https://doi.org/10.1016/j.atmosenv.2021.118322
4601. Learning a data-driven, interpretable, nonlinear model of natural circulation loop dynamics J. Matulis & H. Bindra https://doi.org/10.1016/j.rineng.2026.113455
4602. A Novel ANFIS Framework for Energy Consumption Forecasting in Vietnam V. Phan & D. Nguyen https://doi.org/10.3390/pr14132080
4603. QSAR Regression Models for Predicting the Activity of Inhibitors of Staphylococcus Epidermidis S. Desai https://doi.org/10.4018/IJQSPR.313712
4604. Reconstructing the upwind field of wind turbines using LiDAR data M. Khezri et al. https://doi.org/10.1016/j.seta.2025.104382
4605. Tree‐based flood damage modeling of companies: Damage processes and model performance T. Sieg et al. https://doi.org/10.1002/2017WR020784
4606. 2D Numerical investigation of tsunami bore impact on an elastic emerged plate D. Allo et al. https://doi.org/10.1016/j.oceaneng.2025.121918
4607. Gradient-Free Construction of Active Subspaces for Dimension Reduction in Complex Models with Applications to Neutronics K. Coleman et al. https://doi.org/10.1137/16M1075119
4608. Morphological and structural changes at the Merapi lava dome monitored in 2012–15 using unmanned aerial vehicles (UAVs) H. Darmawan et al. https://doi.org/10.1016/j.jvolgeores.2017.11.006
4609. A Time-Varying Bayesian Compressed Vector Autoregression for Macroeconomic Forecasting N. Aunsri & P. Taveeapiradeecharoen https://doi.org/10.1109/ACCESS.2020.3033203
4610. Tailored group contribution methods designed using machine learning to predict enthalpies in carboxylic acids and anhydrides J. Arzola-Flores et al. https://doi.org/10.1016/j.tca.2024.179923
4611. Assessing COVID-19-Related Excess Mortality Using Multiple Approaches—Italy, 2020–2021 E. Ceccarelli et al. https://doi.org/10.3390/ijerph192416998
4612. Machine Learning-Based Prediction of Gross Primary Productivity in Moist Deciduous Sal Forests of Western Himalayan Foothills of India T. Watham et al. https://doi.org/10.1007/s12524-025-02378-7
4613. Inversion of Cr concentration in farmland soils by coupling hyperspectral remote sensing images with environmental variables: a case study in an agricultural Region of North China H. Wei et al. https://doi.org/10.1007/s11368-026-04342-5
4614. Allometric model to estimate biomass of leave-twigs cajuput (Melaleuca cajuput) at KPH Yogyakarta, Indonesia B. Mulyana et al. https://doi.org/10.1088/1755-1315/724/1/012084
4615. RETRACTED ARTICLE: Digital twin-driven deep learning prediction and adaptive control for coal mine ventilation systems X. Yang & H. Li https://doi.org/10.1038/s41598-025-30513-4
4616. Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters C. Joo et al. https://doi.org/10.1002/int.22700
4617. Forecasting BIST100 Index with Macroeconomic Indicators: A Comparative Analysis with Machine Learning Models S. Turnacıgil et al. https://doi.org/10.17153/oguiibf.1833547
4618. Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare G. Singh https://doi.org/10.1016/j.jjimei.2024.100291
4619. Estimation of ship flue gas emissions in dynamic operational conditions with ANN L. Bilgili & U. Buğra Çelebi https://doi.org/10.1177/1475090220979457
4620. A fully off-grid green steel production: Integrating concentrated solar power, calcium-looping storage, and hydrogen-based direct reduction A. Rashidi et al. https://doi.org/10.1016/j.energy.2026.142211
4621. Combining Spatial Analysis and a Drinking Water Quality Index to Evaluate Monitoring Data H. Li et al. https://doi.org/10.3390/ijerph16030357
4622. Machine learning-based solar radiation prediction across heterogeneous climatic zones using NASA POWER data: a case study in Nigeria O. Faloye et al. https://doi.org/10.3389/frai.2026.1846084
4623. Comparison of Different Remotely Sensed Data Sources for Detection of Presence of Standing Dead Trees Using a Tree-Based Approach M. Jutras-Perreault et al. https://doi.org/10.3390/rs15092223
4624. A combination of large eddy simulation and physics-informed machine learning to predict pore-scale flow behaviours in fibrous porous media: A case study of transient flow passing through a surgical mask M. Mesgarpour et al. https://doi.org/10.1016/j.enganabound.2023.01.010
4625. Overlapping Group Sparse Regularization Technique for Vibration-Based Regional Damage Detection of Structures Z. Luo et al. https://doi.org/10.1142/S0219455425502074
4626. Machine learning in requirements elicitation: a literature review C. Cheligeer et al. https://doi.org/10.1017/S0890060422000166
4627. Signal estimation adaptive algorithm with latch-mechanism for real-time water quality monitoring B. Twarog et al. https://doi.org/10.1016/j.envsoft.2025.106793
4628. Validation and Spatiotemporal Analysis of Surface Net Radiation from CRA/Land and ERA5-Land over the Tibetan Plateau L. Gao et al. https://doi.org/10.3390/atmos14101542
4629. Response Variability of Diffusion Models Applied to Chloride Concentration Profiles from Concrete Structures J. Gonzalez et al. https://doi.org/10.1061/JMCEE7.MTENG-16262
4630. A novel sorting method for liquid metal batteries based on deep learning and sequential features J. Xia et al. https://doi.org/10.1016/j.est.2023.107093
4631. Performance of CMIP6 in rainfall simulation over Didessa, Southwest Ethiopia C. Sime & T. Demissie https://doi.org/10.1007/s12517-025-12238-w
4632. A Bayesian Logistic Regression for Probabilistic Forecasts of the Minimum September Arctic Sea Ice Cover S. Horvath et al. https://doi.org/10.1029/2020EA001176
4633. Effects of missing data imputation methods on univariate blood pressure time series data analysis and forecasting with ARIMA and LSTM N. Niako et al. https://doi.org/10.1186/s12874-024-02448-3
4634. Deep-Learning-Based Adaptive Model for Solar Forecasting Using Clustering S. Malakar et al. https://doi.org/10.3390/en15103568
4635. Efficient design of hydrogen-resistant ultra-high-strength steels via active learning and multiscale characterization C. Shang et al. https://doi.org/10.1016/j.corcom.2025.12.002
4636. Improving estimates of body mass in American black bears using morphometrics and non-linear models M. Barrett et al. https://doi.org/10.2192/URSUS-D-19-00029.1
4637. Analysis of Data Generation and Preparation for Porosity Prediction in Cold Spray using Machine Learning M. Eberle et al. https://doi.org/10.1007/s11666-024-01760-0
4638. Technical validation of a multimodal emotion-adaptive biofeedback system for autonomic regulation using guided breathing C. Srinivasan et al. https://doi.org/10.1038/s41598-026-46105-9
4639. Development and Validation of an IoF-Based Sensing Architecture for Microclimate Monitoring: Quantifying Spatial ET0 Bias in Mediterranean Viticulture O. Oral et al. https://doi.org/10.3390/s26165154
4640. Prediction of pharmacological activities from chemical structures with graph convolutional neural networks M. Sakai et al. https://doi.org/10.1038/s41598-020-80113-7
4641. Infrared Camera Geometric Calibration: A Review and a Precise Thermal Radiation Checkerboard Target A. ElSheikh et al. https://doi.org/10.3390/s23073479
4642. Estimation of Scots pine bark biomass delivered to the wood industry in Northern Germany F. Berendt et al. https://doi.org/10.2478/forj-2022-0019
4643. Terahertz Spectroscopy Characterization and Prediction of the Aging Degree of Polyethylene Pipes Based on PLS J. Ren et al. https://doi.org/10.3390/ma16103652
4644. Particle Swarm Optimized–Support Vector Regression Hybrid Model for Daily Horizon Electricity Demand Forecasting Using Climate Dataset S. Mohanad et al. https://doi.org/10.1051/e3sconf/20186408001
4645. Machine-learning-assisted multiscale modeling strategy for predicting mechanical properties of carbon fiber reinforced polymers G. Zhao et al. https://doi.org/10.1016/j.compscitech.2024.110455
4646. Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran) S. Vafaei et al. https://doi.org/10.3390/rs10020172
4647. Spatial and Spectral Dependencies of Maize Yield Estimation Using Remote Sensing N. Burglewski et al. https://doi.org/10.3390/s24123958
4648. Interaction Simulation of Vadose Zone Water and Groundwater in Cele Oasis: Assessment of the Impact of Agricultural Intensification, Northwestern China D. Xue et al. https://doi.org/10.3390/agriculture12050641
4649. Water Consumption Assessment of Afforestation and Natural Vegetation Areas with a Remote Sensing Approach L. Santarosa et al. https://doi.org/10.3390/w17111597
4650. Denoising variational autoencoders for smart inspection of wafer probe card PCB channels for advancing quality control for semiconductor manufacturing B. Suwattananuruk & C. Chien https://doi.org/10.1016/j.cie.2025.111453
4651. Progressive residual LightGBM (PRLGB) for 5G Quality-of-Service resource allocation prediction P. Barui et al. https://doi.org/10.1007/s44595-026-00003-7
4652. Modeling Growth Kinetics of Escherichia coli and Background Microflora in Hydroponically Grown Lettuce X. You et al. https://doi.org/10.3390/foods13091359
4653. How does “Dr. AI” trigger cyberchondria? An empirical study based on the CMIS framework using a hybrid SEM–ANN approach C. Gu & J. Zhang https://doi.org/10.1007/s12144-025-08899-1
4654. Semi-supervised soft sensor modeling based on reward mechanism T. Li et al. https://doi.org/10.1016/j.measurement.2025.116761
4655. Dynamic modelling of the baseline temperatures for computation of the crop water stress index (CWSI) of a greenhouse cultivated lettuce crop O. Adeyemi et al. https://doi.org/10.1016/j.compag.2018.08.009
4656. Microfluidic impedance cytometry device with N-shaped electrodes for lateral position measurement of single cells/particles D. Yang & Y. Ai https://doi.org/10.1039/C9LC00819E
4657. Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models Z. Yin et al. https://doi.org/10.1002/joc.6435
4658. Evaluation of forecasting methods from selected stock market returns M. Mallikarjuna & R. Rao https://doi.org/10.1186/s40854-019-0157-x
4659. Development of QSAR Models and Web Applications for Predicting hDHFR Inhibitor Bioactivity Using Machine Learning I. Maattallaoui et al. https://doi.org/10.3390/molecules30234618
4660. Algorithm design for wind prediction in Berakit Bay, Bintan Island using Long Short-Term Memory (LSTM) method D. Pratama et al. https://doi.org/10.1088/1755-1315/944/1/012006
4661. Simulating annual runoff retention performance of extensive green roofs: A comparison of four climatic regions in China W. Liu et al. https://doi.org/10.1016/j.jhydrol.2022.127871
4662. Extreme gradient boosting-based multiscale heat source modeling for analysis of solid-state phase transformation in additive manufacturing of Ti-6Al-4V Y. Lee et al. https://doi.org/10.1016/j.jmapro.2024.01.044
4663. Machine Learning-Powered Prediction of molecule Solubility: Paving the Way for environmental, and energy applications I. Aitouhanni et al. https://doi.org/10.1051/bioconf/202410901037
4664. An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning B. Sisman et al. https://doi.org/10.1109/TASLP.2020.3038524
4665. A Developed VMD-DMD Algorithm with Machine Learning Models for Improving Sea Level Predictions: A Case Study of the Mediterranean Coastlines M. Youssef et al. https://doi.org/10.3390/jmse14191865
4666. Estimating the soil water retention curve: Comparison of multiple nonlinear regression approach and random forest data mining technique M. Rastgou et al. https://doi.org/10.1016/j.compag.2020.105502
4667. Kalman filter-based integration of GNSS and InSAR observations for local nonlinear strong deformations D. Tondaś et al. https://doi.org/10.1007/s00190-023-01789-z
4668. Design optimization of OR-PMSM-IPIM using modified slime mold optimization technique for UAV application M. Verma et al. https://doi.org/10.1007/s00202-023-02194-7
4669. Systematic evaluation and validation of reference and library selection methods for deconvolution of cord blood DNA methylation data K. Gervin et al. https://doi.org/10.1186/s13148-019-0717-y
4670. Wind speed and wind direction forecasting using echo state network with nonlinear functions M. Chitsazan et al. https://doi.org/10.1016/j.renene.2018.07.060
4671. A weight recognition method for movable objects in sealed cavity based on supervised learning B. Lv et al. https://doi.org/10.1016/j.measurement.2022.112149
4672. Upgrading the Salinity Index Estimation and Mapping Quality of Soil Salinity Using Artificial Neural Networks in the Lower-Cheliff Plain of Algeria in North Africa A. Ziane et al. https://doi.org/10.1080/07038992.2021.2010523
4673. Optimized Gradient Boosting Models for Adaptive Prediction of Uniaxial Compressive Strength in Carbonate Rocks Using Drilling Data S. Adjei et al. https://doi.org/10.1021/acsomega.4c09603
4674. Improving Short-Term Load Forecasting with Multi-Scale Convolutional Neural Networks and Transformer-Based Multi-Head Attention Mechanisms S. Ding et al. https://doi.org/10.3390/electronics13245023
4675. Robust Vital Sign Monitoring via Condition-Aware Spatial Filtering and Adaptive Time–Frequency Decomposition W. Guo & M. Li https://doi.org/10.1109/JSEN.2026.3693879
4676. Decadal analysis and simulation of land use and land cover changes in Taiwan using machine learning and markov chain models C. Liu & A. Arora https://doi.org/10.1007/s10668-024-05859-w
4677. GEP tree-based computational AI approach to evaluate unconfined compression strength characteristics of Fly ash treated alkali contaminated soils M. Ashfaq et al. https://doi.org/10.1016/j.cscm.2022.e01446
4678. Enhancement of Photovoltaic Performance With Coolant Calcium Chloride: Experimental and Predictive Modeling . Asri et al. https://doi.org/10.1109/ACCESS.2024.3443695
4679. Pathway to identify and assess regional potential soil pollution risk from industrial activities: case of Pearl River Delta region, China X. Wang et al. https://doi.org/10.1080/13504509.2025.2492225
4680. PhenoBot: an automated system for leaf area analysis using deep learning G. Richardson et al. https://doi.org/10.1007/s00425-023-04068-5
4681. Are more data always better? – Machine learning forecasting of algae based on long-term observations D. Atton Beckmann et al. https://doi.org/10.1016/j.jenvman.2024.123478
4682. Congestion Prediction With Big Data for Real-Time Highway Traffic F. Tseng et al. https://doi.org/10.1109/ACCESS.2018.2873569
4683. A Comprehensive Modeling Framework for Air Quality Prediction in Istanbul and CatBoost-SHAP Based Explainability M. Akiner https://doi.org/10.1007/s00024-025-03840-w
4684. Novel multiscale E-metric cross-sample entropy-based cardiac arrhythmia detection and its performance investigation in reference to multiscale cross-sample entropy-based analysis K. Sharma & R. Sunkaria https://doi.org/10.1007/s11760-023-02503-4
4685. A machine learning approach for mapping surface urban heat island using environmental and socioeconomic variables: a case study in a medium-sized Brazilian city M. Furuya et al. https://doi.org/10.1007/s12665-023-11017-8
4686. Neural network approaches for enhanced nitrate management in recirculating aquaculture systems X. Fan et al. https://doi.org/10.1016/j.aquaeng.2025.102650
4687. Evaluating Pre-Loss Normalization Across Multiple Loss Functions in Deep Learning for Multivariate Fluid Flow Prediction U. Kaya & Ö. Ekici https://doi.org/10.1142/S0219876226500295
4688. A General Regression Neural Network Model for Predicting Shale Oil Content Using a Global Dataset of Diverse Oil Shale Deposits S. Sabanov et al. https://doi.org/10.3390/en19184249
4689. Integrating UAV-based multispectral imaging with ground-truth soil nitrogen content for precision agriculture: A case study on paddy field yield estimation using machine learning and plant height monitoring K. Haque et al. https://doi.org/10.1016/j.atech.2025.101542
4690. Assessment of soil mulching field management, and deficit irrigation effect on productivity of watermelon varieties, and AquaCrop model validation B. Gebeyhu & G. Markos https://doi.org/10.1016/j.heliyon.2023.e21632
4691. Combining multisource satellite data to estimate storage variation of a lake in the Rift Valley Basin, Ethiopia W. Asfaw et al. https://doi.org/10.1016/j.jag.2020.102095
4692. Numerical Simulation of a Heavy Precipitation Event in the Vicinity of Madrid-Barajas International Airport: Sensitivity to Initial Conditions, Domain Resolution, and Microphysics Parameterizations P. Bolgiani et al. https://doi.org/10.3390/atmos9090329
4693. A hybrid ontology‐based semantic and machine learning model for the prediction of spring breakup M. De Coste et al. https://doi.org/10.1111/mice.13074
4694. Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning G. Li et al. https://doi.org/10.1038/s42003-020-01638-1
4695. Seismic Stability of Unsupported Rectangular Excavations in Cohesive-Frictional Soils: FELA Simulations and Comparative Analysis Using MARS, GP, and GMDH Models D. Kumar et al. https://doi.org/10.1007/s10706-025-03094-2
4696. Identification of small lakes in Kazakhstan using remote sensing data A. Tolepbayeva et al. https://doi.org/10.2298/IJGI241025005T
4697. Integrating computational 3D-QSAR and pharmacophore modelling in diverse natural phytochemicals library for targeted therapy against breast cancer estrogen receptors S. Islam et al. https://doi.org/10.1016/j.nexres.2024.100012
4698. Recursive Partitioning vs Computerized Adaptive Testing to Reduce the Burden of Health Assessments in Cleft Lip and/or Palate: Comparative Simulation Study C. Harrison et al. https://doi.org/10.2196/26412
4699. Design and Performance Evaluation of a Portable Automated In-Field Cassava Starch Measurement System for Smart Farming Applications S. Asmara https://doi.org/10.62321/issn.1000-1298.2026.6.1
4700. Including the invisible: deep depth-integrated chlorophyll estimates from remote sensing may assist in identifying biologically important areas in oligotrophic coastal margins R. Schoeman et al. https://doi.org/10.5194/bg-22-959-2025
4701. Patient similarity by joint matrix trifactorization to identify subgroups in acute myeloid leukemia F. Vitali et al. https://doi.org/10.1093/jamiaopen/ooy008
4702. Deep evidential transformer with Monte Carlo dropout for uncertainty-aware remaining useful life prediction A. Yilma et al. https://doi.org/10.1016/j.cie.2026.111979
4703. Machine learning for water quality prediction and uncertainty assessment T. Mengistu et al. https://doi.org/10.1016/j.pce.2026.104319
4704. A New Multiscale Deep Learning Model for Daily Runoff Prediction in Snow-Influenced Alpine Catchments P. Luo et al. https://doi.org/10.3390/rs18193309
4705. Asymmetric modeling of fuel consumption in Malaysia T. Siong et al. https://doi.org/10.1016/j.energy.2021.121905
4706. ANNFAA: artificial neural network-based tool for the analysis of Federal Aviation Administration’s rigid pavement systems A. Rezaei Tarahomi et al. https://doi.org/10.1080/10298436.2020.1748627
4707. GraphAT Net: A Deep Learning Approach Combining TrajGRU and Graph Attention for Accurate Cumulonimbus Distribution Prediction T. Zhang et al. https://doi.org/10.3390/atmos14101506
4708. Translating jet noise measurements to near-field level maps with nearest neighbor bilinear smoothing interpolation F. Mobley et al. https://doi.org/10.1121/10.0005737
4709. Blood glucose prediction with deep neural networks using weighted decision level fusion H. Dudukcu et al. https://doi.org/10.1016/j.bbe.2021.08.007
4710. Locating the Italian Radioactive Waste Repository: Issues and Perplexities Arisen from Open Data-Based Analyses about the TO-10 Site (NW Italy) E. Borgogno-Mondino et al. https://doi.org/10.3390/land10090932
4711. Resilience characterized and quantified from physical activity data: A tutorial in R D. Baretta et al. https://doi.org/10.1016/j.psychsport.2022.102361