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Prediction of the solar radiation using RBF neural networks and ground-to-sky images

dc.contributor.authorCrispim, E. M.
dc.contributor.authorFerreira, P. M.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-18T12:08:47Z
dc.date.available2013-02-18T12:08:47Z
dc.date.issued2006
dc.date.updated2013-01-28T16:20:12Z
dc.description.abstractIn this study, Artificial Neural Networks are applied to multistep long term solar radiation prediction. The networks are trained as one-step-ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and Auto-regressive with exogenous inputs solar radiationmodels are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images. The input-output structure of the neural network models is selected using evolutionary computation methods.pt_PT
dc.identifier.citationCrispim, E. M.; Ferreira, P.M.; Ruano, A. E. Prediction of the solar radiation using RBF neural networks and ground-to-sky images, Trabalho apresentado em Global Education Techology Symposium (GETS 2006), In Proceedings of the Global Education Techology Symposium (GETS 2006), Faro, 2006.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2359
dc.language.isoengpor
dc.peerreviewedyespor
dc.titlePrediction of the solar radiation using RBF neural networks and ground-to-sky imagespor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceFaropor
oaire.citation.endPage2por
oaire.citation.startPage1por
oaire.citation.titleGlobal Education Techology Symposium (GETS 2006)por
person.familyNameRuano
person.givenNameAntonio
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

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