Assessing seasonal building thermal adaptation through the acclimatization distance: a GIS-based machine learning framework

IntroductionEnhancing the capacity of residential buildings for maintaining thermal comfort under changing climate conditions is crucial to reducing energy demand and increasing urban resilience. While extensive research has been conducted on energy efficiency at the building scale, less attention h...

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Principais autores:	Daniel Jato-Espino, Francisco Requena-Crespo, Fabio Capra-Ribeiro, Vanessa Moscardó, Maysel Castillo-García
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2026-04-01
coleção:	Frontiers in Sustainable Cities
Assuntos:	acclimatization distance building thermal performance climate-adaptive design geographic information system machine learning seasonal asymmetry
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/frsc.2026.1771368/full
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