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Customisation of green buildings assessment tools based on climatic zoning and experts judgement using K-means clustering and fuzzy AHP

机译:Customisation of green buildings assessment tools based on climatic zoning and experts judgement using K-means clustering and fuzzy AHP

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摘要

Utilising green building regulations and classifications by using well-known assessment tools such as LEED can be challenging in a country with various climates due mainly to specific sustainability priorities for each climate. This paper presents a new framework to customise assessment tools of green buildings for regions or countries with various climates. The framework comprises K-means method to cluster various climates of the region combined with the silhouette value (SV) for clustering verification and local experts' judgement for local customisation of green building assessment tools. The Fuzzy analytical hierarchy process (AHP) is used to adjust the regulations for each climatic zone. The proposed methodology is demonstrated by its application to the realworld case study of Iran. The K-means clustering with SV divides the country into four distinct climatic zones each representing with four meteorological parameters (MP, DTR, CDD, and HDD). Results show each climatic zone can take weights for sustainability categories and criteria based on its climate e.g. higher weight for "Water Efficiency" in zones with low rainfall and higher weight for "Energy and Atmosphere" in zones with heating or cooling needs. Results also show the two categories of "Energy and Atmosphere" and "Water Efficiency" take the largest weights in all zones by an average of almost 27 and 26%. These two categories, alongside with "Sustainable Site", had the most changes in their weights for each climatic zone. The findings of this research reveal the effects of local climates on sustainability priorities of a green building assessment tool.

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