Digital twin based deep learning framework for personalized thermal comfort prediction and energy efficient operation in smart buildings
Abstract The regulation of indoor thermal comfort is a critical aspect of smart building design, significantly influencing energy efficiency and occupant well-being. Traditional comfort models, such as Fanger’s equation and adaptive approaches, often fall short in capturing individual occupant prefe...
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| Main Authors: | Ahmad Almadhor, Nejib Ghazouani, Belgacem Bouallegue, Natalia Kryvinska, Shtwai Alsubai, Moez Krichen, Abdullah Al Hejaili, Gabriel Avelino Sampedro |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-10086-y |
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