Supervised machine learning of thermal comfort under different indoor temperatures using EEG measurements

In this paper, machine learning techniques in conjunction with passive EEG (electroencephalogram) measurement were explored to classify occupants’ real-time thermal comfort states, which have the potential in the future for energy saving through adopting time varying set points when real-time change...

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Bibliographic Details
Main Authors: Shan, Xin, Yang, En-Hua
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/159612
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Institution: Nanyang Technological University
Language: English