61 citations as recorded by crossref.

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9. A Feature Construction Method That Combines Particle Swarm Optimization and Grammatical Evolution I. Tsoulos & A. Tzallas 10.3390/app13148124
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11. Reduced order models for assessing CO2 impacts in shallow unconfined aquifers E. Keating et al. 10.1016/j.ijggc.2016.01.008
12. Bound the Parameters of Neural Networks Using Particle Swarm Optimization I. Tsoulos et al. 10.3390/computers12040082
13. Exploring High‐Dimensional Structure via Axis‐Aligned Decomposition of Linear Projections J. Thiagarajan et al. 10.1111/cgf.13416
14. A Sensitivity Analysis of Two Mesoscale Models: COAMPS and WRF C. Marzban et al. 10.1175/MWR-D-19-0271.1
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17. QFC: A Parallel Software Tool for Feature Construction, Based on Grammatical Evolution I. Tsoulos 10.3390/a15080295
18. Constructing Features Using a Hybrid Genetic Algorithm I. Tsoulos 10.3390/signals3020012
19. Low regularity exponential-type integrators for the “good” Boussinesq equation H. Li & C. Su 10.1093/imanum/drac081
20. Deep learning with support vector data description S. Kim et al. 10.1016/j.neucom.2014.09.086
21. Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges W. Paja 10.3390/e25081223
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23. The examination of the effect of the criterion for neural network’s learning on the effectiveness of the qualitative analysis of multidimensional data D. Jamróz 10.1007/s10115-020-01441-8
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27. A wireless sensor data-based coal mine gas monitoring algorithm with least squares support vector machines optimized by swarm intelligence techniques P. Chen et al. 10.1177/1550147718777440
28. Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant D. Lucas et al. 10.5194/acp-17-13521-2017
29. Adapting the Parameters of RBF Networks Using Grammatical Evolution I. Tsoulos et al. 10.3390/ai4040054
30. Locating the Parameters of RBF Networks Using a Hybrid Particle Swarm Optimization Method I. Tsoulos & V. Charilogis 10.3390/a16020071
31. Sensitivity Analysis of the Spatial Structure of Forecasts in Mesoscale Models: Noncontinuous Model Parameters C. Marzban et al. 10.1175/MWR-D-19-0321.1
32. A Two-Phase Evolutionary Method to Train RBF Networks I. Tsoulos et al. 10.3390/app12052439
33. A Review and Experimental Comparison of Multivariate Decision Trees L. Canete-Sifuentes et al. 10.1109/ACCESS.2021.3102239
34. An extensive analysis of the interaction between missing data types, imputation methods, and supervised classifiers U. Garciarena & R. Santana 10.1016/j.eswa.2017.07.026
35. On the effect of model parameters on forecast objects C. Marzban et al. 10.5194/gmd-11-1577-2018
36. To what extent does ENSO rectify the tropical Pacific mean state? M. Xue & T. Li 10.1007/s00382-023-06750-6
37. What should we do when a model crashes? Recommendations for global sensitivity analysis of Earth and environmental systems models R. Sheikholeslami et al. 10.5194/gmd-12-4275-2019
38. A Rule-Based Method to Locate the Bounds of Neural Networks I. Tsoulos et al. 10.3390/knowledge2030024
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43. Applying Bounding Techniques on Grammatical Evolution I. Tsoulos et al. 10.3390/computers13050111
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45. Extremely simple classifier based on fuzzy logic and gene expression programming J. Kluska & M. Madera 10.1016/j.ins.2021.05.041
46. Evaluation of scale-aware subgrid mesoscale eddy models in a global eddy-rich model B. Pearson et al. 10.1016/j.ocemod.2017.05.007
47. Uncertainty Analysis of Simulations of the Turn‐of‐the‐Century Drought in the Western United States G. Anderson et al. 10.1029/2017JD027824
48. Constructing the Bounds for Neural Network Training Using Grammatical Evolution I. Tsoulos et al. 10.3390/computers12110226
49. A novel Bayesian method for variable selection and estimation in binary quantile regression M. Dao et al. 10.1002/sam.11591
50. Multi-Layer Hybrid (MLH) balancing technique: A combined approach to remove data imbalance M. Islam & H. Mustafa 10.1016/j.datak.2022.102105
51. New Approach Based on Termite's Hill Building for Prediction of Successful Simulations in Climate Models M. Rahmani et al. 10.4018/IJSIR.2017070103
52. Machine Learning Predictions of a Multiresolution Climate Model Ensemble G. Anderson & D. Lucas 10.1029/2018GL077049
53. Selective Neuron Re-Computation (SNRC) for Error-Tolerant Neural Networks S. Liu et al. 10.1109/TC.2021.3056992
54. The Construction of a Majority-Voting Ensemble Based on the Interrelation and Amount of Information of Features F. Aydın & Z. Aslan 10.1093/comjnl/bxz118
55. Semisupervised Tangent Space Discriminant Analysis Y. Zhou & S. Sun 10.1155/2015/706180
56. Result-Based Re-computation for Error-Tolerant Classification by a Support Vector Machine S. Liu et al. 10.1109/TAI.2020.3028321
57. The use of Lorentzian distance metric in classification problems Y. Kerimbekov et al. 10.1016/j.patrec.2016.09.006
58. Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification M. Loog 10.1109/TPAMI.2015.2452921
59. Voting Margin: A Scheme for Error-Tolerant k Nearest Neighbors Classifiers for Machine Learning S. Liu et al. 10.1109/TETC.2019.2963268
60. A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data R. de Oliveira & D. Martens 10.3390/app11167274
61. When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores J. Wang et al. 10.1007/s00521-017-3102-9