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Predicting the greenhouse inside air temperature with RBF neural networks

dc.contributor.authorFerreira, P. M.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-13T10:03:12Z
dc.date.available2013-02-13T10:03:12Z
dc.date.issued2001
dc.date.updated2013-01-30T15:37:26Z
dc.description.abstractThe application of the Radial Basis Function (RBF) Neural Network (NN) to greenhouse inside air temperature modelling has been previously investigated (Ferreira et al., 2000a). In those studies, the inside air temperature is modelled as a function of the inside relative humidity and of the outside temperature and solar radiation. A second-order model structure previously selected (Cunha et al., 1996) in the context of dynamic temperature models identification, is used.pt_PT
dc.identifier.citationFerreira, P. M.; Ruano, A. E. Predicting the Greenhouse Inside Air Temperature with RBF Neural Networks, Trabalho apresentado em 2nd IFAC-CIGR Workshop on Intelligent Control for Agricultural Applications (ICAA'2001), In 2nd IFAC-CIGR Workshop on Intelligent Control for Agricultural Applications (ICAA'2001), Bali, 2001.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2336
dc.language.isoengpor
dc.peerreviewedyespor
dc.subjectNeural Networkspor
dc.subjectGreenhouse Environmental Controlpor
dc.subjectModellingpor
dc.subjectRadial Basis Functionspor
dc.subjectPredictionpor
dc.titlePredicting the greenhouse inside air temperature with RBF neural networkspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceBalipor
oaire.citation.endPage72por
oaire.citation.startPage67por
oaire.citation.title2nd IFAC-CIGR Workshop on Intelligent Control for Agricultural Applications (ICAA'2001)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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