Abstract Traditional urban building energy modeling often overlooks the complexity of spatial configurations and mutual shading effects, thereby limiting its accuracy. This study proposes a novel, interpretable, data-dr...
Interpretable Urban Building Energy Modeling by Heterogeneous Graph Neural Networks: A Case Study of Residential Blocks in Wuhan
Vorheriger Beitrag
