Privacy preserved and decentralized thermal comfort prediction model for smart buildings using federated learning
Thermal comfort is a crucial element of smart buildings that assists in improving, analyzing, and realizing intelligent structures. Energy consumption forecasts for such smart buildings are crucial owing to the intricate decision-making processes surrounding resource efficiency. Machine learning (ML...
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| Autores principales: | , , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
PeerJ Inc.
2024-02-01
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| Colección: | PeerJ Computer Science |
| Materias: | |
| Acceso en línea: | https://peerj.com/articles/cs-1899.pdf |
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