Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/57617
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dc.contributor.authorKangalli, Uyar, S.G.-
dc.contributor.authorDal, B.-
dc.contributor.authorOzbay, B.K.-
dc.date.accessioned2024-07-28T17:17:40Z-
dc.date.available2024-07-28T17:17:40Z-
dc.date.issued2024-
dc.identifier.issn0360-1323-
dc.identifier.urihttps://doi.org/10.1016/j.buildenv.2024.111768-
dc.identifier.urihttps://hdl.handle.net/11499/57617-
dc.description.abstractControlling carbon emissions is critical to mitigating the negative environmental impacts of carbon emissions, such as global warming and climate change. Identifying the factors that affect building emissions is important because they contribute significantly to global emissions. The study aimed to determine the building characteristics that affect building emissions for residential buildings in Istanbul using the MARS algorithm. The MARS algorithm was also used to estimate building emissions based on the energy performance certificate data for each building. The study revealed that building characteristics have specific thresholds that affect building emissions differently depending on whether they are above or below these thresholds. The feature selection analysis revealed that the thermal insulation properties, specifically the wall_u value, roof_u value, and window_u value, had the greatest impact on building emissions. Other factors identified were building age, heating power, and floor height. These factors alone explain about 77 % of the building emissions. The analysis identified the interactions between building characteristics that affect building emissions. This enables common, appropriate solutions to be developed in terms of building characteristics to reduce building emissions. © 2024 Elsevier Ltden_US
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofBuilding and Environmenten_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBuilding carbon emissionsen_US
dc.subjectFeature selection analysisen_US
dc.subjectMARS algorithmen_US
dc.subjectRegression analysisen_US
dc.subjectResidential buildingsen_US
dc.subjectCarbonen_US
dc.subjectEnvironmental impacten_US
dc.subjectFeature Selectionen_US
dc.subjectGlobal warmingen_US
dc.subjectHousingen_US
dc.subjectThermal insulationen_US
dc.subjectBuilding carbon emissionen_US
dc.subjectBuilding characteristicsen_US
dc.subjectCarbon emissionsen_US
dc.subjectFeature selection analyseen_US
dc.subjectFeatures selectionen_US
dc.subjectGlobal warming and climate changesen_US
dc.subjectIstanbulen_US
dc.subjectMARS algorithmen_US
dc.subjectResidential buildingen_US
dc.subjectU valuesen_US
dc.subjectRegression analysisen_US
dc.titleModeling building carbon emissions by using MARS algorithm: A case of Istanbulen_US
dc.typeArticleen_US
dc.identifier.volume262en_US
dc.departmentPamukkale Universityen_US
dc.identifier.doi10.1016/j.buildenv.2024.111768-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid57190620607-
dc.authorscopusid59218075400-
dc.authorscopusid59218216500-
dc.identifier.scopus2-s2.0-85198520476en_US
dc.identifier.wosWOS:001272108400001en_US
dc.institutionauthor-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeArticle-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
crisitem.author.dept08.08. Econometrics-
crisitem.author.dept08.01. Management Information Systems-
crisitem.author.dept08.08. Econometrics-
Appears in Collections:İktisadi ve İdari Bilimler Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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