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On the application of clustering techniques for office buildings’ energy and thermal comfort classification

Stavrakakis Georgios, Kolokotsa Dionysia, Nikolaou Theodoros, Skias Ioannis

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URIhttp://purl.tuc.gr/dl/dias/4CF0A02F-1380-41CF-931C-2391C9E19418-
Identifierhttps://doi.org/10.1109/TSG.2012.2215059-
Languageen-
Extent15 pagesen
TitleOn the application of clustering techniques for office buildings’ energy and thermal comfort classificationen
CreatorStavrakakis Georgiosen
CreatorΣταυρακακης Γεωργιοςel
CreatorKolokotsa Dionysiaen
CreatorΚολοκοτσα Διονυσιαel
CreatorNikolaou Theodorosen
CreatorΝικολαου Θεοδωροςel
CreatorSkias Ioannisen
CreatorΣκιας Ιωαννηςel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryThe aim of this paper is to develop and propose an integrated classification method for the determination of office buildings' energy and thermal comfort rating classes. The applications of five clustering techniques: Hierarchical, K-Means, Gaussian Mixture Models, Fuzzy, and Neural algorithms to a large building dataset are tested in order to investigate the appropriate method for establishing energy and thermal comfort classifications. For the clustering results testing, three internal validity indices: the Silhouette, the Davies Bouldin, and the Dunn Index have been applied, in order to select the appropriate number of clusters and the most efficient algorithm for each case. The proposed classification approach is also evaluated through comparisons with the methodologies that are recommended by the European standards. The classification results are used for a parametric study of common buildings' characteristics in each rating class, in order to provide with a tool for adopting improvement recommendations for buildings' energy efficiency.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-15-
Date of Publication2012-
SubjectEnergy efficiency in buildingsen
Bibliographic CitationΤ. Nikolaou, D. Kolokotsa, G. Stavrakakis, I. Skias,”On the application of clustering techniques for office buildings’ energy and thermal comfort classification, ” IEEE Trans. on Sm. Grid, vol.3 ,no.4 , pp. 2196 - 2210, Dec. 2012.doi: 10.1109/TSG.2012.2215059 en

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