A Comparison of Different Deep Learning Model Architectures and Training Strategy for Urban Energy Modeling
Abstract
To address the pressing issue of urbanization and its significant energy consumption, the development of urban building energy modeling (UBEM) is an ongoing mission. This research explores the integration of machine learning (ML) models into UBEM. through a comprehensive analysis of various deep learning approaches, this work aims to enhance our understanding of UBEM and pave the way for more in-depth ML-UBEM studies.
This paper has been withdrawn.
