Multi-Task Learning for Concurrent Prediction of Thermal Comfort, Sensation and Preference in Winters

Multi-Task Learning for Concurrent Prediction of Thermal Comfort, Sensation and Preference in Winters

Indoor thermal comfort immensely impacts the health and performance of occupants. Therefore, researchers and engineers have proposed numerous computational models to estimate thermal comfort (TC). Given the impetus toward energy efficiency, the current focus is on data-driven TC prediction solutions...

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Bibliographic Details
Main Authors:	Betty Lala, Hamada Rizk, Srikant Manas Kala, Aya Hagishima
Format:	Article
Language:	English
Published:	MDPI AG 2022-05-01
Series:	Buildings
Subjects:	thermal comfort machine learning multi-task learning deep learning classification prediction
Online Access:	https://www.mdpi.com/2075-5309/12/6/750

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