Interactive effects of hyperparameter optimization techniques and data characteristics on the performance of machine learning algorithms for building energy metamodeling

Metamodeling is a promising technique for alleviating the computational burden of building energy simulation. Although various machine learning (ML) algorithms have been applied, the interactive effects of multiple factors on ML algorithm performance remain unclear. In this study, six popular ML alg...

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Bibliographic Details

Published in:	Case Studies in Thermal Engineering
Main Authors:	Binghui Si, Zhenyu Ni, Jiacheng Xu, Yanxia Li, Feng Liu
Format:	Article
Language:	English
Published:	Elsevier 2024-03-01
Subjects:	Building energy efficiency Metamodel Machine learning Hyperparameter optimization Data characteristic
Online Access:	http://www.sciencedirect.com/science/article/pii/S2214157X24001552