The use of artificial neural network to evaluate insulation thickness and life cycle costs: Pipe insulation application

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dc.contributor.authorKayfeci, Muhammet
dc.contributor.authorYabanova, Ismail
dc.contributor.authorKecebas, Ali
dc.date.accessioned2024-09-29T15:54:58Z
dc.date.available2024-09-29T15:54:58Z
dc.date.issued2014
dc.departmentKarabük Üniversitesien_US
dc.description.abstractThis paper reports on the use of artificial neural networks (ANNs) to predict insulation thickness and life cycle costs (LCCs) for pipe insulation applications. Data were collected from insulation markets and some data calculated by using LCC analysis. Using the collected data set and LCC analysis results for training, a three-layer feedforward ANN model based on a backpropagation algorithm was developed. This model was used for predicting optimum insulation thickness, total cost, cost saving and payback period. The effects on the predicted parameter of heating degree-days are discussed in detail. The results show that the network yields a maximum correlation coefficient with minimum mean absolute relative error and root mean square error. The developed ANN model has a very practical use of determining the optimum thickness of insulation for any location in the world when just the input parameters of the ANN model are known. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.applthermaleng.2013.11.017
dc.identifier.endpage378en_US
dc.identifier.issn1359-4311
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-84890304199en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage370en_US
dc.identifier.urihttps://doi.org/10.1016/j.applthermaleng.2013.11.017
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4391
dc.identifier.volume63en_US
dc.identifier.wosWOS:000331021600038en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofApplied Thermal Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEnergy savingen_US
dc.subjectPipe insulationen_US
dc.subjectLCC analysisen_US
dc.subjectANN modellingen_US
dc.subjectOptimizationen_US
dc.titleThe use of artificial neural network to evaluate insulation thickness and life cycle costs: Pipe insulation applicationen_US
dc.typeArticleen_US

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