An experimental review on deep learning architectures for time series forecasting P Lara-Benítez, M Carranza-García, JC Riquelme International journal of neural systems 31 (03), 2130001, 2021 | 373 | 2021 |
Incremental wrapper-based gene selection from microarray data for cancer classification R Ruiz, JC Riquelme, JS Aguilar-Ruiz Pattern Recognition 39 (12), 2383-2392, 2006 | 362 | 2006 |
Energy time series forecasting based on pattern sequence similarity FM Alvarez, A Troncoso, JC Riquelme, JSA Ruiz IEEE Transactions on Knowledge and Data Engineering 23 (8), 1230-1243, 2010 | 331 | 2010 |
Electricity market price forecasting based on weighted nearest neighbors techniques AT Lora, JMR Santos, AG Expósito, JLM Ramos, JCR Santos IEEE Transactions on Power Systems 22 (3), 1294-1301, 2007 | 302 | 2007 |
Minería de datos: Conceptos y tendencias JC Riquelme Santos, R Ruiz, K Gilbert Inteligencia Artificial: Revista Iberoamericana de Inteligencia Artificial …, 2006 | 237 | 2006 |
A survey on data mining techniques applied to electricity-related time series forecasting F Martínez-Álvarez, A Troncoso, G Asencio-Cortés, JC Riquelme Energies 8 (11), 13162-13193, 2015 | 210 | 2015 |
A framework for evaluating land use and land cover classification using convolutional neural networks M Carranza-García, J García-Gutiérrez, JC Riquelme Remote Sensing 11 (3), 274, 2019 | 202 | 2019 |
Temporal convolutional networks applied to energy-related time series forecasting P Lara-Benítez, M Carranza-García, JM Luna-Romera, JC Riquelme applied sciences 10 (7), 2322, 2020 | 192 | 2020 |
Preliminary comparison of techniques for dealing with imbalance in software defect prediction D Rodriguez, I Herraiz, R Harrison, J Dolado, JC Riquelme Proceedings of the 18th international conference on evaluation and …, 2014 | 159 | 2014 |
Coronavirus optimization algorithm: a bioinspired metaheuristic based on the COVID-19 propagation model F Martínez-Álvarez, G Asencio-Cortés, JF Torres, D Gutiérrez-Avilés, ... Big data 8 (4), 308-322, 2020 | 147 | 2020 |
Evolutionary learning of hierarchical decision rules JS Aguilar-Ruiz, JC Riquelme, M Toro IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 33 …, 2003 | 141 | 2003 |
An evolutionary algorithm to discover numeric association rules J Mata, JL Alvarez, JC Riquelme Proceedings of the 2002 ACM symposium on Applied computing, 590-594, 2002 | 137 | 2002 |
An evolutionary approach to estimating software development projects JS Aguilar-Ruiz, I Ramos, JC Riquelme, M Toro Information and Software Technology 43 (14), 875-882, 2001 | 126 | 2001 |
Discovering numeric association rules via evolutionary algorithm J Mata, JL Alvarez, JC Riquelme Pacific-Asia conference on knowledge discovery and data mining, 40-51, 2002 | 122 | 2002 |
Big data analytics for discovering electricity consumption patterns in smart cities R Pérez-Chacón, JM Luna-Romera, A Troncoso, F Martínez-Álvarez, ... Energies 11 (3), 683, 2018 | 119 | 2018 |
A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables J García-Gutiérrez, F Martínez-Álvarez, A Troncoso, JC Riquelme Neurocomputing 167, 24-31, 2015 | 117 | 2015 |
Finding representative patterns with ordered projections JC Riquelme, JS Aguilar-Ruiz, M Toro pattern recognition 36 (4), 1009-1018, 2003 | 115 | 2003 |
Local models-based regression trees for very short-term wind speed prediction A Troncoso, S Salcedo-Sanz, C Casanova-Mateo, JC Riquelme, L Prieto Renewable Energy 81, 589-598, 2015 | 96 | 2015 |
Mining numeric association rules with genetic algorithms J Mata, JL Alvarez, JC Riquelme Artificial Neural Nets and Genetic Algorithms: Proceedings of the …, 2001 | 90 | 2001 |
Evolutionary generalized radial basis function neural networks for improving prediction accuracy in gene classification using feature selection F Fernández-Navarro, C Hervás-Martínez, R Ruiz, JC Riquelme Applied Soft Computing 12 (6), 1787-1800, 2012 | 79 | 2012 |