Leveraging Machine Learning to Forecast Neighborhood Energy Use in Early Design Stages: A Preliminary Application

The need for energy efficiency in neighborhood-scale architectural design is driven by environmental imperatives and escalating energy costs. This study identifies three key phases in a design process framework where machine learning can be applied to optimize energy consumption in early design stag...

Descripció completa

Dades bibliogràfiques

Autors principals:	Andrea Giuseppe di Stefano, Matteo Ruta, Gabriele Masera, Simi Hoque
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-11-01
Col·lecció:	Buildings
Matèries:	predictive analysis energy efficiency strategies data-driven neighborhood design design process framework urban building energy modeling
Accés en línia:	https://www.mdpi.com/2075-5309/14/12/3866
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!