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...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/159612 |