Short term wind speed prediction based on evolutionary support vector regression algorithms S Salcedo-Sanz, EG Ortiz-Garcı, ÁM Pérez-Bellido, A Portilla-Figueras, ... Expert Systems with Applications 38 (4), 4052-4057, 2011 | 261 | 2011 |
Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction S Salcedo-Sanz, ÁM Pérez-Bellido, EG Ortiz-García, A Portilla-Figueras, ... Renewable Energy 34 (6), 1451-1457, 2009 | 237 | 2009 |
Mortality impact of extreme winter temperatures J Díaz, R García, C López, C Linares, A Tobías, L Prieto International Journal of Biometeorology 49, 179-183, 2005 | 203 | 2005 |
Feature selection in machine learning prediction systems for renewable energy applications S Salcedo-Sanz, L Cornejo-Bueno, L Prieto, D Paredes, R García-Herrera Renewable and Sustainable Energy Reviews 90, 728-741, 2018 | 172 | 2018 |
Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization–Extreme learning machine approach S Salcedo-Sanz, A Pastor-Sánchez, L Prieto, A Blanco-Aguilera, ... Energy Conversion and Management 87, 10-18, 2014 | 170 | 2014 |
Seeding evolutionary algorithms with heuristics for optimal wind turbines positioning in wind farms B Saavedra-Moreno, S Salcedo-Sanz, A Paniagua-Tineo, L Prieto, ... Renewable Energy 36 (11), 2838-2844, 2011 | 161 | 2011 |
Accurate short-term wind speed prediction by exploiting diversity in input data using banks of artificial neural networks S Salcedo-Sanz, AM Perez-Bellido, EG Ortiz-García, A Portilla-Figueras, ... Neurocomputing 72 (4-6), 1336-1341, 2009 | 129 | 2009 |
Offshore wind farm design with the coral reefs optimization algorithm S Salcedo-Sanz, D Gallo-Marazuela, A Pastor-Sánchez, L Carro-Calvo, ... Renewable Energy 63, 109-115, 2014 | 110 | 2014 |
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 |
Minimum extreme temperatures over Peninsular Spain L Prieto, RG Herrera, J Díaz, E Hernández, T del Teso Global and Planetary Change 44 (1-4), 59-71, 2004 | 87 | 2004 |
A coral reefs optimization algorithm with harmony search operators for accurate wind speed prediction S Salcedo-Sanz, A Pastor-Sánchez, J Del Ser, L Prieto, ZW Geem Renewable Energy 75, 93-101, 2015 | 85 | 2015 |
Prediction of hourly O3 concentrations using support vector regression algorithms EG Ortiz-García, S Salcedo-Sanz, ÁM Pérez-Bellido, JA Portilla-Figueras, ... Atmospheric Environment 44 (35), 4481-4488, 2010 | 83 | 2010 |
Multi-task learning for the prediction of wind power ramp events with deep neural networks M Dorado-Moreno, N Navarin, PA Gutiérrez, L Prieto, A Sperduti, ... Neural Networks 123, 401-411, 2020 | 67 | 2020 |
Short‐term wind speed prediction in wind farms based on banks of support vector machines EG Ortiz‐García, S Salcedo‐Sanz, ÁM Pérez‐Bellido, J Gascón‐Moreno, ... Wind Energy 14 (2), 193-207, 2011 | 67 | 2011 |
A long-term perspective of wind power output variability N Kirchner-Bossi, R García Herrera, L Prieto, RM Trigo Royal Meteorological Society (Great Britain), 2014 | 52 | 2014 |
Short-term wind speed prediction by hybridizing global and mesoscale forecasting models with artificial neural networks SS Sanz, A Perez-Bellido, E Ortiz-Garcia, A Portilla-Figueras, L Prieto, ... 2008 Eighth International Conference on Hybrid Intelligent Systems, 608-612, 2008 | 44 | 2008 |
Randomization-based machine learning in renewable energy prediction problems: Critical literature review, new results and perspectives J Del Ser, D Casillas-Perez, L Cornejo-Bueno, L Prieto-Godino, ... Applied Soft Computing 118, 108526, 2022 | 43 | 2022 |
Evolutionary computation approaches for real offshore wind farm layout: A case study in northern Europe S Salcedo-Sanz, D Gallo-Marazuela, A Pastor-Sánchez, L Carro-Calvo, ... Expert Systems with Applications 40 (16), 6292-6297, 2013 | 42 | 2013 |
A parallel CFD model for wind farms M Avila, A Folch, G Houzeaux, B Eguzkitza, L Prieto, D Cabezón Procedia Computer Science 18, 2157-2166, 2013 | 41 | 2013 |
Synoptic conditions leading to extremely high temperatures in Madrid R García, L Prieto, J Díaz, E Hernández, T Del Teso Annales Geophysicae 20 (2), 237-245, 2002 | 39 | 2002 |