Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89558
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dc.contributorDepartment of Building Services Engineering-
dc.creatorTsang, TW-
dc.creatorMui, KW-
dc.creatorWong, LT-
dc.creatorYu, W-
dc.date.accessioned2021-04-09T08:51:21Z-
dc.date.available2021-04-09T08:51:21Z-
dc.identifier.issn1750-8975-
dc.identifier.urihttp://hdl.handle.net/10397/89558-
dc.language.isoenen_US
dc.publisherEarthscan Publications Ltden_US
dc.rights© 2020 Informa UK Limited, trading as Taylor & Francis Groupen US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Intelligent Buildings International on 12 Sep 2020 (Published online), available online: http://www.tandfonline.com/10.1080/17508975.2020.1803788en US
dc.titleBayesian updates for indoor environmental quality (IEQ) acceptance model for residential buildingsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage17-
dc.identifier.epage32-
dc.identifier.volume13-
dc.identifier.issue1-
dc.identifier.doi10.1080/17508975.2020.1803788-
dcterms.abstractAn accurate indoor environmental quality (IEQ) model is essential to design and maintain a comfortable indoor environment. Due to the complexity of IEQ modelling and subjective nature of IEQ responses, there is a need to update the subjective–objective relationship of IEQ model when new information is available. In this study, a Bayesian approach for IEQ model updating is proposed to systematically relate new subjective IEQ responses towards the environment to the existing beliefs. With a selected target sample size and an acceptable error, the statistical significance of data is evaluated and incorporated into the updated IEQ model. Bayesian updating framework is able to enhance the accuracy of IEQ prediction and shall be a useful tool for managerial decision-making in maintaining a comfortable indoor environment.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIntelligent buildings international, 2021, v. 13, no. 1, p. 17-32-
dcterms.isPartOfIntelligent buildings international-
dcterms.issued2021-
dc.identifier.scopus2-s2.0-85102865730-
dc.identifier.eissn1756-6932-
dc.description.validate202104 bcrc-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0665-n03-
dc.identifier.SubFormID831-
dc.description.fundingSourceRGC-
dc.description.fundingSourceOthers-
dc.description.fundingTextRGC: PolyU 152088/17E, B-Q59V-
dc.description.fundingTextOthers: The Hong Kong Polytechnic University GYBFN-
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
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