| SMOTE-RSB *: a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets … E Ramentol, Y Caballero, R Bello, F Herrera Knowledge and information systems 33, 245-265, 2012 | 531 | 2012 |
| A review on methods and software for fuzzy cognitive maps G Felix, G Nápoles, R Falcon, W Froelich, K Vanhoof, R Bello Artificial intelligence review 52, 1707-1737, 2019 | 297 | 2019 |
| Multiple instance learning F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ... Multiple instance learning: foundations and algorithms, 17-33, 2016 | 146 | 2016 |
| On the convergence of sigmoid fuzzy cognitive maps G Nápoles, E Papageorgiou, R Bello, K Vanhoof Information Sciences 349, 154-171, 2016 | 114 | 2016 |
| IFROWANN: imbalanced fuzzy-rough ordered weighted average nearest neighbor classification E Ramentol, S Vluymans, N Verbiest, Y Caballero, R Bello, C Cornelis, ... IEEE Transactions on Fuzzy Systems 23 (5), 1622-1637, 2014 | 114 | 2014 |
| Two-step particle swarm optimization to solve the feature selection problem R Bello, Y Gomez, A Nowe, MM Garcia Seventh international conference on intelligent systems design and …, 2007 | 109 | 2007 |
| Two-steps learning of Fuzzy Cognitive Maps for prediction and knowledge discovery on the HIV-1 drug resistance G Nápoles, I Grau, R Bello, R Grau Expert Systems with Applications 41 (3), 821-830, 2014 | 103 | 2014 |
| Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm E Ramentol, I Gondres, S Lajes, R Bello, Y Caballero, C Cornelis, ... Engineering Applications of Artificial Intelligence 48, 134-139, 2016 | 88 | 2016 |
| ANN-QSAR model for selection of anticancer leads from structurally heterogeneous series of compounds H González-Díaz, I Bonet, C Terán, E De Clercq, R Bello, MM García, ... European journal of medicinal chemistry 42 (5), 580-585, 2007 | 82 | 2007 |
| Learning and convergence of fuzzy cognitive maps used in pattern recognition G Nápoles, E Papageorgiou, R Bello, K Vanhoof Neural Processing Letters 45, 431-444, 2017 | 81 | 2017 |
| Fuzzy cognitive maps based models for pattern classification: Advances and challenges G Nápoles, M Leon Espinosa, I Grau, K Vanhoof, R Bello Soft Computing Based Optimization and Decision Models: To Commemorate the …, 2018 | 78 | 2018 |
| Analysis of the efficacy of a Two-Stage methodology for ant colony optimization: Case of study with TSP and QAP A Puris, R Bello, F Herrera Expert Systems with Applications 37 (7), 5443-5453, 2010 | 77 | 2010 |
| Variable mesh optimization for continuous optimization problems A Puris, R Bello, D Molina, F Herrera Soft Computing 16, 511-525, 2012 | 71 | 2012 |
| Aplicaciones de la inteligencia artificial R Bello, ZZ García, MM García, A Reynoso Ediciones de la Noche, Guadalajara, Jalisco, México 970 (27), 0177, 2002 | 66 | 2002 |
| Rough sets in the soft computing environment R Bello, JL Verdegay Information Sciences 212, 1-14, 2012 | 64 | 2012 |
| Granular computing: at the junction of rough sets and fuzzy sets R Bello, R Falcón, W Pedrycz Springer Science & Business Media, 2008 | 58 | 2008 |
| SMOTE-FRST: a new resampling method using fuzzy rough set theory E Ramentol, N Verbiest, R Bello, Y Caballero, C Cornelis, F Herrera Uncertainty modeling in knowledge engineering and decision making, 800-805, 2012 | 56 | 2012 |
| Rough cognitive networks G Nápoles, I Grau, E Papageorgiou, R Bello, K Vanhoof Knowledge-Based Systems 91, 46-61, 2016 | 55 | 2016 |
| Rough set theory: a true landmark in data analysis A Abraham, R Falcón, R Bello Springer Science & Business Media, 2009 | 54 | 2009 |
| Fuzzy-rough cognitive networks G Nápoles, C Mosquera, R Falcon, I Grau, R Bello, K Vanhoof Neural Networks 97, 19-27, 2018 | 50 | 2018 |
