Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12104/64561
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dc.contributor.authorRangel, E.
dc.contributor.authorAlanis, A.Y.
dc.contributor.authorRicalde, L.J.
dc.contributor.authorArana-Daniel, N.
dc.contributor.authorLopez-Franco, C.
dc.date.accessioned2015-11-19T18:49:32Z-
dc.date.available2015-11-19T18:49:32Z-
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/20.500.12104/64561-
dc.description.abstractThis paper deals with a novel training algorithm for a neural network architecture applied to solar radiation time series prediction. The proposed training algorithm is based in a novel bio-inspired aging model-particle swarm optimization (BAM-PSO). The BAM-PSO based algorithm is employed to update the synaptic weights of the neural network. The size of the regression vector is determined by means of the Cao methodology. The proposed structure captures efficiently the complex nature of the solar radiation time series. The proposed model is trained and tested using real data values for solar radiation. © Springer International Publishing Switzerland 2014.
dc.titleBio-inspired aging model particle swarm optimization neural network training for solar radiation forecasting
dc.typeArticle
dc.relation.ispartofjournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartofvolume8827
dc.relation.ispartofpage682
dc.relation.ispartofpage689
dc.contributor.affiliationRangel, E., CUCEI, Universidad de Guadalajara, Apartado Postal 51-71, Col. Las AguilasZapopan, Jalisco, Mexico; Alanís, A.Y., CUCEI, Universidad de Guadalajara, Apartado Postal 51-71, Col. Las AguilasZapopan, Jalisco, Mexico; Ricalde, L.J., UADY, Av. Industrias no Contaminantes por Periferico Norte, Apdo. Postal 115 CordemexMerida, Yucatan, Mexico; Arana-Daniel, N., CUCEI, Universidad de Guadalajara, Apartado Postal 51-71, Col. Las AguilasZapopan, Jalisco, Mexico; López-Franco, C., CUCEI, Universidad de Guadalajara, Apartado Postal 51-71, Col. Las AguilasZapopan, Jalisco, Mexico
dc.relation.isReferencedByScopus
dc.identifier.urlhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84921343423&partnerID=40&md5=7e6949f4d6dfc1ece2554074a1785583
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