Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/6686
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dc.contributor.authorTurhan, Cihan-
dc.contributor.authorKazanasmaz, Zehra Tuğçe-
dc.contributor.authorGökçen Akkurt, Gülden-
dc.date.accessioned2018-01-15T11:39:36Z
dc.date.available2018-01-15T11:39:36Z
dc.date.issued2017-08
dc.identifier.citationTurhan, C., Kazanasmaz, T., and Gökçen Akkurt, G. (2017). Performance indices of soft computing models to predict the heat load of buildings in terms of architectural indicators. Journal of Thermal Engineering, 3(4), 1358-1374. doi:10.18186/journal-of-thermal-engineering.330180en_US
dc.identifier.issn2148-7847
dc.identifier.issn2148-7847-
dc.identifier.urihttp://doi.org/10.18186/journal-of-thermal-engineering.330180
dc.identifier.urihttp://hdl.handle.net/11147/6686
dc.description.abstractThis study estimates the heat load of buildings in Izmir/Turkey by three soft computing (SC) methods; Artificial Neural Networks (ANNs), Fuzzy Logic (FL) and Adaptive Neuro-based Fuzzy Inference System (ANFIS) and compares their prediction indices. Obtaining knowledge about what the heat load of buildings would be in architectural design stage is necessary to forecast the building performance and take precautions against any possible failure. The best accuracy and prediction power of novel soft computing techniques would assist the practical way of this process. For this purpose, four inputs, namely, wall overall heat transfer coefficient, building area/ volume ratio, total external surface area and total window area/total external surface area ratio were employed in each model of this study. The predicted heat load is evaluated comparatively using simulation outputs. The ANN model estimated the heat load of the case apartments with a rate of 97.7% and the MAPE of 5.06%; while these ratios are 98.6% and 3.56% in Mamdani fuzzy inference systems (FL); 99.0% and 2.43% in ANFIS. When these values were compared, it was found that the ANFIS model has become the best learning technique among the others and can be applicable in building energy performance studies.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK -- 109M450),en_US
dc.language.isoenen_US
dc.publisherYıldız Teknik Üniversitesien_US
dc.relationinfo:eu-repo/grantAgreement/TUBITAK/MAG/109M450en_US
dc.relation.ispartofJournal of Thermal Engineeringen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectANFISen_US
dc.subjectFuzzy logicen_US
dc.subjectHeat loaden_US
dc.subjectResidential buildingsen_US
dc.subjectSoft computing methodsen_US
dc.titlePerformance indices of soft computing models to predict the heat load of buildings in terms of architectural indicatorsen_US
dc.typeArticleen_US
dc.authoridTR103337en_US
dc.authoridTR28229en_US
dc.authoridTR130569en_US
dc.contributor.departmentIzmir Institute of Technology. Mechanical Engineering
dc.contributor.departmentIzmir Institute of Technology. Mechanical Engineeringen_US
dc.contributor.departmentIzmir Institute of Technology. Energy Systems Engineeringen_US
dc.contributor.departmentIzmir Institute of Technology. Architectureen_US
dc.identifier.volume3en_US
dc.identifier.issue4en_US
dc.identifier.startpage1358en_US
dc.identifier.endpage1374en_US
dc.identifier.wosWOS:000407804200006
dc.identifier.scopusSCOPUS:2-s2.0-85034989833
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.18186/journal-of-thermal-engineering.330180-
dc.relation.doi10.18186/journal-of-thermal-engineering.330180en_US
dc.coverage.doi10.18186/journal-of-thermal-engineering.330180en_US
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairetypeArticle-
crisitem.author.deptDepartment of Architecture-
crisitem.author.deptDepartment of Energy Systems Engineering-
Appears in Collections:Architecture / Mimarlık
Energy Systems Engineering / Enerji Sistemleri Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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