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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Podrobná bibliografie

Hlavní autoři:	Sidra Abbas, Shtwai Alsubai, Gabriel Avelino Sampedro, Mideth Abisado, Ahmad Almadhor, Tai-hoon Kim
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	PeerJ Inc. 2024-02-01
Edice:	PeerJ Computer Science
Témata:	Thermal comfort Smart buildings Federated deep learning Machine learning Privacy
On-line přístup:	https://peerj.com/articles/cs-1899.pdf
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!