Title Evolutionary artificial neural networks for accurate solar radiation prediction
Authors Guijo-Rubio D. , DURAN ROSAL, ANTONIO MANUEL, Gutiérrez P.A. , Gómez-Orellana A.M. , Casanova-Mateo C. , Sanz-Justo J. , Salcedo-Sanz S. , Hervás-Martínez C.
External publication No
Means Energy
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
JCR Impact 7.14700
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089243647&doi=10.1016%2fj.energy.2020.118374&partnerID=40&md5=6adb578082c4f4f363e8730013402154
Publication date 01/11/2020
ISI 000606796000001
Scopus Id 2-s2.0-85089243647
DOI 10.1016/j.energy.2020.118374
Abstract This paper evaluates the performance of different evolutionary neural network models in a problem of solar radiation prediction at Toledo, Spain. The prediction problem has been tackled exclusively from satellite-based measurements and variables, which av
Keywords Evolutionary algorithms; Forecasting; Machine learning; Solar radiation; Evolutionary artificial neural networks; Evolutionary neural network; Extreme learning machine; Machine learning approaches; Ra
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