Modelling of a thermal insulation system based on the coldest temperature conditions by using artificial neural networks to determine performance of building for wall types in Turkey

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dc.contributor.authorTosun, M.
dc.contributor.authorDincer, K.
dc.date.accessioned2020-03-26T18:15:19Z
dc.date.available2020-03-26T18:15:19Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn formation of building external envelope, as two important criteria, climatic data and wall types must be taken into consideration. In the selection of wall type, the thickness of thermal insulation layer (d(i)) must be calculated. As a new approach, this study proposes determining the thermal insulation layer by using artificial neural network (ANN) technique. In this technique five different wall types in four different climatic regions in Turkey have been selected. The ANN was trained and tested by using MATLAB toolbox on a personal computer. As ANN input parameters, U(w), T(e,Met), T(e,TSE), R(wt), and q(TSE) were used, while d(i) was the output parameter. It was found that the maximum mean absolute percentage error (MRE, %) is less than 7.658%. R(2) (%) for the training data were found ranging about from 99.68 to 99.98 and R(2) for the testing data varied between 97.55 and 99.96. These results show that ANN model can be used as a reliable modeling method of d(i) studies. (C) 2010 Elsevier Ltd and IIR. All rights reserved.en_US
dc.identifier.doi10.1016/j.ijrefrig.2010.08.001en_US
dc.identifier.endpage373en_US
dc.identifier.issn0140-7007en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage362en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.ijrefrig.2010.08.001
dc.identifier.urihttps://hdl.handle.net/20.500.12395/26653
dc.identifier.volume34en_US
dc.identifier.wosWOS:000286343500036en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIER SCI LTDen_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF REFRIGERATION-REVUE INTERNATIONALE DU FROIDen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectInsulationen_US
dc.subjectThermal analysisen_US
dc.subjectWallen_US
dc.subjectBuildingen_US
dc.subjectCoolingen_US
dc.subjectNeural networken_US
dc.titleModelling of a thermal insulation system based on the coldest temperature conditions by using artificial neural networks to determine performance of building for wall types in Turkeyen_US
dc.typeArticleen_US

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