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Neural networks applied to temperature estimation in school buildings

dc.contributor.authorCrispim, E. M.
dc.contributor.authorMartins, P. M.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-11T10:45:50Z
dc.date.available2013-02-11T10:45:50Z
dc.date.issued2004
dc.date.updated2013-01-27T20:50:50Z
dc.description.abstractThis paper present an Artificial Neural Network (NN) applied to the modelling of inside air temperature in a building school. This modelling is a function of outside air temperature and solar radiation, inside air humidity and state of windows and doors. This NN is a one step-ahead predictive model, and is intended to be the basis model for longer prediction horizons. The NN model employed was the Radial Basis Functions Neural Network (RBFNN, trained using the Levenberg-Maquardt algorithm. The structure selection of the best fitted model RBFNN was accomplished by multiobjective genetic algorithms (MOGA).por
dc.identifier.citationCrispim, E. M.; Martins, P. M.; Ruano, A. E. Neural Networks applied to Temperature Estimation in School Buildings, Trabalho apresentado em Workshop on Intelligent Buildings: Rational use of energy in school buildings in Algarve, In Proceedings of the Workshop on Intelligent Buildings: Rational use of energy in school buildings in Algarve, Faro, 2004.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2289
dc.language.isoengpor
dc.peerreviewedyespor
dc.titleNeural networks applied to temperature estimation in school buildingspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceFaropor
oaire.citation.endPage4por
oaire.citation.startPage1por
oaire.citation.titleWorkshop on Intelligent Buildings: Rational use of energy in school buildings in Algarvepor
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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