Neural networks: An overview of early research, current frameworks and new challenges A Prieto, B Prieto, EM Ortigosa, E Ros, F Pelayo, J Ortega, I Rojas Neurocomputing 214, 242-268, 2016 | 361 | 2016 |
Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation J González, I Rojas, J Ortega, H Pomares, FJ Fernandez, AF Díaz IEEE Transactions on Neural Networks 14 (6), 1478-1495, 2003 | 267 | 2003 |
Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps E De la Hoz, E De La Hoz, A Ortiz, J Ortega, A Martínez-Álvarez Knowledge-Based Systems 71, 322-338, 2014 | 209 | 2014 |
PCA filtering and probabilistic SOM for network intrusion detection E De la Hoz, E De La Hoz, A Ortiz, J Ortega, B Prieto Neurocomputing 164, 71-81, 2015 | 208 | 2015 |
A hybrid meta-heuristic for multi-objective vehicle routing problems with time windows R Baños, J Ortega, C Gil, AL Márquez, F De Toro Computers & industrial engineering 65 (2), 286-296, 2013 | 206 | 2013 |
Self-organized fuzzy system generation from training examples I Rojas, H Pomares, J Ortega, A Prieto IEEE transactions on fuzzy systems 8 (1), 23-36, 2000 | 196 | 2000 |
Time series analysis using normalized PG-RBF network with regression weights I Rojas, H Pomares, JL Bernier, J Ortega, B Pino, FJ Pelayo, A Prieto Neurocomputing 42 (1-4), 267-285, 2002 | 194 | 2002 |
A simulated annealing-based parallel multi-objective approach to vehicle routing problems with time windows R Baños, J Ortega, C Gil, A Fernández, F De Toro Expert Systems with Applications 40 (5), 1696-1707, 2013 | 184 | 2013 |
A new clustering technique for function approximation J González, H Rojas, J Ortega, A Prieto IEEE Transactions on Neural Networks 13 (1), 132-142, 2002 | 182 | 2002 |
A systematic approach to a self-generating fuzzy rule-table for function approximation H Pomares, I Rojas, J Ortega, J Gonzalez, A Prieto IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 30 …, 2000 | 138 | 2000 |
A new multi-objective wrapper method for feature selection–accuracy and stability analysis for BCI J González, J Ortega, M Damas, P Martín-Smith, JQ Gan Neurocomputing 333, 407-418, 2019 | 127 | 2019 |
PSFGA: a parallel genetic algorithm for multiobjective optimization F De Toro, J Ortega, J Fernández, A Díaz Proceedings 10th Euromicro Workshop on Parallel, Distributed and Network …, 2002 | 98 | 2002 |
A single front genetic algorithm for parallel multi-objective optimization in dynamic environments M Cámara, J Ortega, F de Toro Neurocomputing 72 (16-18), 3570-3579, 2009 | 93 | 2009 |
Accelerating OpenFlow switching with network processors Y Luo, P Cascon, E Murray, J Ortega Proceedings of the 5th ACM/IEEE Symposium on Architectures for Networking …, 2009 | 86 | 2009 |
Separation of sources: A geometry-based procedure for reconstruction of n-valued signals CG Puntonet, A Prieto, C Jutten, M Rodriguez-Alvarez, J Ortega Signal Processing 46 (3), 267-284, 1995 | 86 | 1995 |
PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation F de Toro Negro, J Ortega, E Ros, S Mota, B Paechter, JM Martın Parallel Computing 30 (5-6), 721-739, 2004 | 80 | 2004 |
A quantitative study of fault tolerance, noise immunity, and generalization ability of MLPs JL Bernier, J Ortega, E Ros, I Rojas, A Prieto Neural Computation 12 (12), 2941-2964, 2000 | 77 | 2000 |
Improved RAN sequential prediction using orthogonal techniques M Salmeron, J Ortega, CG Puntonet, A Prieto Neurocomputing 41 (1-4), 153-172, 2001 | 70 | 2001 |
Parallel processing for multi-objective optimization in dynamic environments M Cámara, J Ortega, FJ Toro 2007 IEEE International Parallel and Distributed Processing Symposium, 1-8, 2007 | 67 | 2007 |
Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off J León, JJ Escobar, A Ortiz, J Ortega, J González, P Martín-Smith, JQ Gan, ... Plos one 15 (6), e0234178, 2020 | 66 | 2020 |