72 citations as recorded by crossref.

1. TRIDENT-DE: Triple-Operator Differential Evolution with Adaptive Restarts and Greedy Refinement V. Charilogis et al.
2. Training Artificial Neural Networks Using a Global Optimization Method That Utilizes Neural Networks I. Tsoulos & A. Tzallas
3. Random Bits Forest: a Strong Classifier/Regressor for Big Data Y. Wang et al.
4. Resolving learning rates adaptively by locating stochastic non-negative associated gradient projection points using line searches D. Kafka & D. Wilke
5. Optimizing the Bounds of Neural Networks Using a Novel Simulated Annealing Method I. Tsoulos et al.
6. The parametric sensitivity of CAM5's MJO J. Boyle et al.
7. Learning Functions and Classes Using Rules I. Tsoulos
8. A simple and efficient architecture for trainable activation functions A. Apicella et al.
9. FT4cip: A new functional tree for classification in class imbalance problems L. Cañete-Sifuentes et al.
10. Value proposition operationalization in peer-to-peer platforms using machine learning J. Ramos-Henríquez et al.
11. Train Neural Networks with a Hybrid Method That Incorporates a Novel Simulated Annealing Procedure I. Tsoulos et al.
12. A Feature Construction Method That Combines Particle Swarm Optimization and Grammatical Evolution I. Tsoulos & A. Tzallas
13. Random bits regression: a strong general predictor for big data Y. Wang et al.
14. Reduced order models for assessing CO2 impacts in shallow unconfined aquifers E. Keating et al.
15. Bound the Parameters of Neural Networks Using Particle Swarm Optimization I. Tsoulos et al.
16. Exploring High‐Dimensional Structure via Axis‐Aligned Decomposition of Linear Projections J. Thiagarajan et al.
17. A Sensitivity Analysis of Two Mesoscale Models: COAMPS and WRF C. Marzban et al.
18. Improving the Generalization Abilities of Constructed Neural Networks with the Addition of Local Optimization Techniques I. Tsoulos et al.
19. Tackling Climate Change with Machine Learning D. Rolnick et al.
20. A multivariate analysis and machine learning approach to assess the impact of climate change on water quality N. Salehi Siavashani et al.
21. Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation I. Yamane et al.
22. From Initialization to Convergence: A Three-Stage Technique for Robust RBF Network Training I. Tsoulos et al.
23. QFC: A Parallel Software Tool for Feature Construction, Based on Grammatical Evolution I. Tsoulos
24. Improving the Performance of Constructed Neural Networks with a Pre-Train Phase I. Tsoulos et al.
25. Neural DE: An Evolutionary Method Based on Differential Evolution Suitable for Neural Network Training I. Tsoulos & V. Charilogis
26. Constructing Features Using a Hybrid Genetic Algorithm I. Tsoulos
27. Low regularity exponential-type integrators for the “good” Boussinesq equation H. Li & C. Su
28. Gen2Gen: Efficiently Training Artificial Neural Networks Using a Series of Genetic Algorithms I. Tsoulos & V. Charilogis
29. Deep learning with support vector data description S. Kim et al.
30. Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges W. Paja
31. Ensemble simulations of inertial confinement fusion implosions R. Nora et al.
32. 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
33. RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution I. Tsoulos et al.
34. RN-SMOTE: Reduced Noise SMOTE based on DBSCAN for enhancing imbalanced data classification A. Arafa et al.
35. Introducing an Evolutionary Method to Create the Bounds of Artificial Neural Networks I. Tsoulos et al.
36. An automated design process for short pulse laser driven opacity experiments M. Martin et al.
37. RFCL: A new under-sampling method of reducing the degree of imbalance and overlap R. Zhang et al.
38. 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.
39. Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant D. Lucas et al.
40. Adapting the Parameters of RBF Networks Using Grammatical Evolution I. Tsoulos et al.
41. Locating the Parameters of RBF Networks Using a Hybrid Particle Swarm Optimization Method I. Tsoulos & V. Charilogis
42. Training Neural Networks with a Procedure Guided by BNF Grammars I. Tsoulos  & V. Charilogis
43. Sensitivity Analysis of the Spatial Structure of Forecasts in Mesoscale Models: Noncontinuous Model Parameters C. Marzban et al.
44. A Two-Phase Evolutionary Method to Train RBF Networks I. Tsoulos et al.
45. Local Crossover: A New Genetic Operator for Grammatical Evolution I. Tsoulos et al.
46. Using Optimization Techniques in Grammatical Evolution I. Tsoulos et al.
47. Combining Constructed Artificial Neural Networks with Parameter Constraint Techniques to Achieve Better Generalization Properties I. Tsoulos et al.
48. A Review and Experimental Comparison of Multivariate Decision Trees L. Canete-Sifuentes et al.
49. An extensive analysis of the interaction between missing data types, imputation methods, and supervised classifiers U. Garciarena & R. Santana
50. On the effect of model parameters on forecast objects C. Marzban et al.
51. To what extent does ENSO rectify the tropical Pacific mean state? M. Xue & T. Li
52. What should we do when a model crashes? Recommendations for global sensitivity analysis of Earth and environmental systems models R. Sheikholeslami et al.
53. Utilizing a Bounding Procedure Based on Simulated Annealing to Effectively Locate the Bounds for the Parameters of Radial Basis Function Networks I. Tsoulos et al.
54. A Rule-Based Method to Locate the Bounds of Neural Networks I. Tsoulos et al.
55. Finding plausible and diverse variants of a climate model. Part II: development and validation of methodology A. Karmalkar et al.
56. Approximation trees: statistical reproducibility in model distillation Y. Zhou et al.
57. Healing Intelligence: A Bio-Inspired Metaheuristic Optimization Method Using Recovery Dynamics V. Charilogis & I. Tsoulos
58. A genetic algorithm approach to optimising random forests applied to class engineered data E. Elyan & M. Gaber
59. Calibrated simplex-mapping classification R. Heese et al.
60. Low-regularity integrators for the “good” Boussinesq equation with linearly decreasing additional derivative requirements H. Li & C. Su
61. Earth system simulations suggest that the Proterozoic ocean was greener but less productive P. Liu et al.
62. Applying Bounding Techniques on Grammatical Evolution I. Tsoulos et al.
63. Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models W. Paja et al.
64. Extremely simple classifier based on fuzzy logic and gene expression programming J. Kluska & M. Madera
65. Evaluation of scale-aware subgrid mesoscale eddy models in a global eddy-rich model B. Pearson et al.
66. Uncertainty Analysis of Simulations of the Turn‐of‐the‐Century Drought in the Western United States G. Anderson et al.
67. Constructing the Bounds for Neural Network Training Using Grammatical Evolution I. Tsoulos et al.
68. A novel Bayesian method for variable selection and estimation in binary quantile regression M. Dao et al.
69. Multi-Layer Hybrid (MLH) balancing technique: A combined approach to remove data imbalance M. Islam & H. Mustafa
70. New Approach Based on Termite's Hill Building for Prediction of Successful Simulations in Climate Models M. Rahmani et al.
71. Introducing a New Genetic Operator Based on Differential Evolution for the Effective Training of Neural Networks I. Tsoulos et al.
72. Machine Learning Predictions of a Multiresolution Climate Model Ensemble G. Anderson & D. Lucas