A networked smart home system based on recurrent neural networks and reinforcement learning
With the widespread application of smart home systems, the optimal design of smart home systems has received considerable research attention. This paper puts forward a network smart home system design scheme based on the analysis of the indoor environment and the forecast of the future indoor enviro...
Guardado en:
Autores principales: | Zhongwang Li, Bin Deng |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Taylor & Francis Group
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/e988470e4170493cb3e42d0f895f32ce |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Enhancing traffic capacity of multilayer networks with two logical layers by link deletion
por: Jinlong Ma, et al.
Publicado: (2022) -
Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots
por: Jorge Montoya‐Cháirez, et al.
Publicado: (2022) -
Hierarchical speed control for autonomous electric vehicle through deep reinforcement learning and robust control
por: Guangfei Xu, et al.
Publicado: (2022) -
Decentralized event‐triggered robust MPC for large‐scale networked Lipchitz non‐linear control systems
por: Saeid GHorbani, et al.
Publicado: (2021) -
Synchronisation of multiple neural networks via event‐triggered time‐varying delay hybrid impulsive control
por: Xiaoli Ruan, et al.
Publicado: (2021)