Smart City Planning by Estimating Energy Efficiency of Buildings by Extreme Learning Machine

dc.contributor.authorErtugrul, Omer Faruk
dc.contributor.authorKaya, Yilmaz
dc.date.accessioned2024-12-24T19:23:59Z
dc.date.available2024-12-24T19:23:59Z
dc.date.issued2016
dc.departmentSiirt Üniversitesi
dc.description4th International Istanbul Smart Grid Congress and Fair (ICSG) -- APR 20-21, 2016 -- Istanbul, TURKEY
dc.description.abstractEstimation of energy efficiency is one of the major issues in smart city planning. Although, there are some papers about estimation of energy efficiency of the buildings, there is still a requirement of an effective method that can be used in all climatic zones. Therefore, extreme learning method (ELM), which is a training method for single hidden layer neural network, was employed in the dataset that contains the properties of buildings such as shape, area and height and cooling and heating loads were calculated. Achieved results by ELM were compared with the results in the literature and the results obtained by some popular machine learning methods such as artificial neural network, linear regression, and etc. Obtained results by ELM found acceptable.
dc.description.sponsorshipRepubl Turkey, Minist EU Affairs,Turkiye Cumhuriyeti Kultur Turizm Bakanligi,KOSGEB,TEDAS,TEIAS,Istanbul Buyuksehir Belediyesi,Turkish Electro Technol,Energy Business Council, Foreign Econ Relat Board,Istanbul Kanalizasyon Idaresi,BOTAS,IGDAS Gokyuzuyle Arkadas,Istanbul Ticaret Odasi,Istabul Sanayi Odasi,UHE,UFI,Elder,GAZBIR,TENVA,Turk Sanayici Isadamlari VAKFI,Organize Sanayi Bolgeleri Dernegi,Teknoloji Ar Ge Bilim Inouasyon Dernegi,TURKCELL,Vodafone,LUNA,STATUEAZ,SABAH,HITACHI,KOHLER,ORACLE,aselsan,ERICSSON,NETAS,SIEMENS,Microsoft,best,HHB EXPO,Republ Turkey, Minist Sci Ind & Technol,Republ Turkey, Minist Environm & Urbanisat,Republ Turkey, Minist Energy & Nat Resources,EPDK, Republ Turkey,Istanbul Metropolitan Municipal,Ugetam,IEEE SMARTGRID,IEEE Power & Energy Soc
dc.identifier.endpage51
dc.identifier.isbn978-1-5090-0866-7
dc.identifier.scopus2-s2.0-84978657369
dc.identifier.scopusqualityN/A
dc.identifier.startpage47
dc.identifier.urihttps://hdl.handle.net/20.500.12604/5795
dc.identifier.wosWOS:000389660400008
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2016 4th International Istanbul Smart Grid Congress and Fair (Icsg)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectSmart City
dc.subjectEnergy Efficiency of Building
dc.subjectExtreme Learning Machine
dc.titleSmart City Planning by Estimating Energy Efficiency of Buildings by Extreme Learning Machine
dc.typeConference Object

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