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Model comparison for temperature estimation inside buildings

dc.contributor.authorCrispim, E. M.
dc.contributor.authorMartins, P. M.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-11T11:49:06Z
dc.date.available2013-02-11T11:49:06Z
dc.date.issued2005
dc.date.updated2013-01-26T19:34:10Z
dc.description.abstractThis paper presents a comparison between a physical model and an artificial neural network model (NN) for temperature estimation inside a building room. Despite the obvious advantages of the physical model for structure optimisation purposes, this paper will test the performance of neural models for inside temperature estimation. The great advantage of the NN model is a big reduction of human effort time, because it is not needed to develop the structural geometry and structural thermal capacities and to simulate, which consumes a great human effort and great computation time. The NN model deals with this problem as a “black box” problem. We describe the use of the Radial Basis Function (RBF), the training method and a multi-objective genetic algorithm for optimisation/selection of the RBF neural network inputs and number of neurons.por
dc.identifier.citationCrispim, E. M.; Martins, P. M.; Ruano, A. E. Model comparison for temperature estimation inside buildings, Trabalho apresentado em IEEE International Workshop on Soft Computing Applications, In Proceedings of the IEEE International Workshop on Soft Computing Applications, Szeged, 2005.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2296
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherIEEEpor
dc.subjectEstimationpor
dc.subjectFeedforward neural networkspor
dc.subjectGenetic algorithmspor
dc.subjectNonlinear systemspor
dc.titleModel comparison for temperature estimation inside buildingspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceSzegedpor
oaire.citation.endPage6por
oaire.citation.startPage1por
oaire.citation.titleInternational Workshop on Soft Computing Applicationspor
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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