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dc.contributor.authorSedano, Javier
dc.contributor.authorVillar, José Ramón
dc.contributor.authorCuriel Herrera, Leticia Elena 
dc.contributor.authorCal, Enrique de la
dc.contributor.authorCorchado, Emilio 
dc.date.accessioned2024-02-05T11:13:07Z
dc.date.available2024-02-05T11:13:07Z
dc.date.issued2010
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10259/8578
dc.descriptionTrabajo presentado en: International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, 2010es
dc.description.abstractImproving the detection of thermal insulation failures in buildings includes the development of models for heating process and fabric gain -heat flux through exterior walls in the building-. Thermal insulation standards are now contractual obligations in new buildings, the energy efficiency in the case of buildings constructed before the regulations adopted is still an open issue, and the assumption is that it will be based on heat flux and conductivity measurement. A three-step procedure is proposed in this study that begins by considering the local building and heating system regulations as well as the specific features of the climate zone. Firstly, the dynamic thermal performance of different variables is specifically modeled. Secondly, an exploratory projection pursuit method called Cooperative Maximum-Likelihood Hebbian Learning is used to extract the relevant features. Finally, a supervised neural model and identification techniques are applied, in order to detect the heat flux through exterior walls in the building. The reliability of the proposed method is validated for a winter zone, associated to several cities in Spain.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherSpringer Natureen
dc.relation.ispartofLecture Notes in Computer Science. 2010, V. 6098, p. 636-645en
dc.subjectComputational Intelligenceen
dc.subjectSoft computing Systemsen
dc.subjectIdentification Systemsen
dc.subjectArtificial Neural Networksen
dc.subjectNon-linear Systemsen
dc.subject.otherInformáticaes
dc.subject.otherComputer scienceen
dc.titleModelling of Heat Flux in Building Using Soft-Computing Techniquesen
dc.typeinfo:eu-repo/semantics/bookPartes
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-642-13033-5_65es
dc.identifier.doi10.1007/978-3-642-13033-5_65
dc.identifier.essn1611-3349
dc.volume.number6098es
dc.page.initial636es
dc.page.final645es
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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