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dc.contributor.authorMateo, Fernando
dc.contributor.authorCarrasco, Juan José
dc.contributor.authorSellami, Abderrahim
dc.contributor.authorMillán Giraldo, Mónica
dc.contributor.authorDomínguez, Manuel
dc.contributor.authorSoria-Olivas, Emilio
dc.date.accessioned2014-04-16T14:55:51Z
dc.date.available2014-04-16T14:55:51Z
dc.date.issued2013
dc.identifier.citationExpert Systems with Applications Volume 40, Issue 4, March 2013, Pages 1061–1068ca_CA
dc.identifier.issn0957-4174
dc.identifier.urihttp://hdl.handle.net/10234/90498
dc.description.abstractEfficient management of energy in buildings saves a very important amount of resources (both economic and technological). As a consequence, there is a very active research in this field. One of the keys of energy management is the prediction of the variables that directly affect building energy consumption and personal comfort. Among these variables, one can highlight the temperature in each room of a building. In this work we apply different machine learning techniques along with other classical ones for predicting the temperatures in different rooms. The obtained results demonstrate the validity of these techniques for predicting temperatures and, therefore, for the establishment of optimal policies of energy consumption.ca_CA
dc.format.extent7 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherElsevierca_CA
dc.relation.isPartOfExpert Systems with Applications, 2013, vol. 40, no 4ca_CA
dc.rightsCopyright © 2012 Elsevier Ltd. All rights reserved.ca_CA
dc.subjectForecastingca_CA
dc.subjectEnergy efficiencyca_CA
dc.subjectMachine learningca_CA
dc.subjectTime seriesca_CA
dc.titleMachine learning methods to forecast temperature in buildingsca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1016/j.eswa.2012.08.030
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccessca_CA
dc.relation.publisherVersionhttp://www.sciencedirect.com/science/article/pii/S0957417412009918ca_CA


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  • LSI_Articles [272]
    Articles de publicacions periòdiques escrits per professors del Departament de Llenguatges i Sistemes Informàtics

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