文献
J-GLOBAL ID:202202220060780496
整理番号:22A0902602
多エネルギー産業公園のためのマルチエージェント深層強化学習に基づくエネルギー管理【JST・京大機械翻訳】
Energy management based on multi-agent deep reinforcement learning for a multi-energy industrial park
著者 (16件):
Zhu Dafeng
(Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China)
,
Zhu Dafeng
(Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China)
,
Zhu Dafeng
(Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, China)
,
Yang Bo
(Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China)
,
Yang Bo
(Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China)
,
Yang Bo
(Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, China)
,
Liu Yuxiang
(Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China)
,
Liu Yuxiang
(Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China)
,
Liu Yuxiang
(Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, China)
,
Wang Zhaojian
(Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China)
,
Wang Zhaojian
(Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China)
,
Wang Zhaojian
(Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, China)
,
Ma Kai
(Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China)
,
Guan Xinping
(Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China)
,
Guan Xinping
(Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China)
,
Guan Xinping
(Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, China)
資料名:
Applied Energy
(Applied Energy)
巻:
311
ページ:
Null
発行年:
2022年
JST資料番号:
A0097A
ISSN:
0306-2619
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)