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Predicting solar radiation with RBF neural networks

dc.contributor.authorFerreira, P. M.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-11T11:00:32Z
dc.date.available2013-02-11T11:00:32Z
dc.date.issued2004
dc.date.updated2013-01-27T20:30:16Z
dc.description.abstractIn this paper radial basis function neural networks are applied to the prediction of global solar radiation. The networks are employed as one-step-ahead predictors of the solar radiation time series and iterated over time to obtain longer term predictions. Several models are compared varying the input dimension, the network size and the time series sampling rate. An empiric rule is proposed for network input selection. All networks are trained using one data set and evaluated for prediction performance on unseen data. Predictor performance is assessed taking root mean square measures of the error over the prediction horizon. The aim of this work is to select a model to be used in a climate simulator for an hydroponic greenhouse.por
dc.identifier.citationFerreira, P. M.; Ruano, A. E. Predicting solar radiation with RBF neural networks. Trabalho apresentado em 6th Portuguese Conference on Automatic Control (Controlo 2004), In 6th Portuguese Conference on Automatic Control (Controlo 2004), Faro, 2004.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2292
dc.language.isoengpor
dc.peerreviewedyespor
dc.subjectNeural Networkspor
dc.subjectGreenhouse Environmental Controlpor
dc.subjectRadial Basis Functionspor
dc.subjectSolar Radiation Predictionpor
dc.subjectTime Seriespor
dc.titlePredicting solar radiation with RBF neural networkspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceFaropor
oaire.citation.endPage6por
oaire.citation.startPage1por
oaire.citation.title6th Portuguese Conference on Automatic Control (Controlo 2004)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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