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检索条件"主题词=Deep deterministic policy gradient algorithm"
32 条 记 录,以下是1-10 订阅
排序:
Information-Based Patrol Speed Control Method for Rail-Guided Robot System Using deep deterministic policy gradient algorithm  18th
Information-Based Patrol Speed Control Method for Rail-Guide...
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18th International Conference on Intelligent Autonomous Systems (IAS)
作者: Lee, Hosun Kwon, Jaesung Lee, Sungon Chong, Nak Young Yang, Woosung Japan Adv Inst Sci & Technol Sch Informat Sci Nomi Ishikawa Japan Kwangwoon Univ Sch Robot Seoul South Korea Hanyang Univ Dept Robot Ansan South Korea
To manage the safety of multi-use facilities, many CCTVs and alarm sensors are used, however, they cannot replace patrol tasks to check site conditions from multiple directions. The developed rail-guided smart patrol ... 详细信息
来源: 评论
Optimal operation of regional integrated energy system based on multi-agent deep deterministic policy gradient algorithm
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ENERGY REPORTS 2022年 8卷 932-939页
作者: Xu, Bohan Xiang, Yue Sichuan Univ Coll Elect Engn Chengdu Peoples R China
The complex energy coupling and uncertainties of renewable energy and load make the dynamic scheduling of the integrated energy system (IES) very difficult. Therefore, an optimal operation method based on the multi-ag... 详细信息
来源: 评论
A deep deterministic policy gradient algorithm Based Controller with Adjustable Learning Rate for DC-AC Inverters  2
A Deep Deterministic Policy Gradient Algorithm Based Control...
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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023
作者: Ye, Jian Mei, Sen Guo, Huanyu Zhao, Di Zhang, Xinan School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China School of Electrical Electronic and Computer Engineering University of Western Australia Perth Australia
This paper proposes an inverter control algorithm based on the deep deterministic policy gradient (DDPG) with adjustable learning rates. This algorithm retains the advantages of model-free control of the inverter and ... 详细信息
来源: 评论
Reinforcement learning control method for real-time hybrid simulation based on deep deterministic policy gradient algorithm
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STRUCTURAL CONTROL & HEALTH MONITORING 2022年 第10期29卷
作者: Li, Ning Tang, Jichuan Li, Zhong-Xian Gao, Xiuyu Tianjin Univ Sch Civil Engn Tianjin 300350 Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn Singapore Singapore Tianjin Univ Minist Educ Key Lab Coast Civil Struct Safety Tianjin Peoples R China Tianjin Univ Key Lab Earthquake Engn Simulat & Seism Resilienc China Earthquake Adm Tianjin Peoples R China MTS Corp Eden Prairie MN USA
The tracking performance of an actuation transfer system in a real-time hybrid simulation (RTHS) frequently faces accuracy and robustness challenges under constraints and complicated environments with uncertainties. T... 详细信息
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Control Method for PEMFC Using Improved deep deterministic policy gradient algorithm
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FRONTIERS IN ENERGY RESEARCH 2021年 9卷
作者: Li, Jiawen Li, Yaping Yu, Tao South China Univ Technol Coll Elect Power Guangzhou Peoples R China China Elect Power Res Inst Nanjing Peoples R China
A data-driven PEMFC output voltage control method is proposed. Moreover, an Improved deep deterministic policy gradient algorithm is proposed for this method. The algorithm introduces three techniques: Clipped multipl... 详细信息
来源: 评论
Continuous decision-making for autonomous driving at intersections using deep deterministic policy gradient
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IET INTELLIGENT TRANSPORT SYSTEMS 2022年 第12期16卷 1669-1681页
作者: Li, Guofa Li, Shenglong Li, Shen Qu, Xingda Shenzhen Univ Coll Mechatron & Control Engn Inst Human Factors & Ergon 3688 Nanhai Ave Shenzhen Guangdong Peoples R China Univ Wisconsin Dept Civil & Environm Engn Madison WI 53706 USA
Intersections have been identified as the most complex and accident-prone traffic scenarios on road. Making appropriate decisions at intersections for driving safety, efficiency, and comfort become a challenging task ... 详细信息
来源: 评论
Experimental validation of a semi-active fuzzy control strategy based on deep reinforcement learning for a piezoelectric smart isolation system
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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2025年 144卷
作者: Lin, Tzu-Kang Tappiti, Chandrasekhara Lu, Lyan-Ywan Lin, Ting-Kuan Natl Yang Ming Chiao Tung Univ Dept Civil Engn Hsinchu City Taiwan Natl Cheng Kung Univ Dept Civil Engn Tainan Taiwan
The high-tech industry, commanding a substantial portion of the global market, remains highly susceptible to disruptions caused by earthquakes because its products rely heavily on vibration-sensitive equipment. Moreov... 详细信息
来源: 评论
Energy management strategy for hybrid electric vehicles based on deep reinforcement learning with consideration of electric drive system thermal characteristics
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ENERGY CONVERSION AND MANAGEMENT 2025年 332卷
作者: Qin, Juhuan Huang, Haozhong Lu, Hualin Li, Zhaojun Guangxi Univ Coll Mech Engn Nanning 530004 Peoples R China
deep reinforcement learning has emerged as a promising candidate for online optimised energy management in hybrid vehicles. However, previous studies have not considered the impact of the overall thermal characteristi... 详细信息
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Parametric Dueling DQN- and DDPG-Based Approach for Optimal Operation of Microgrids
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PROCESSES 2024年 第9期12卷 1822-1822页
作者: Huang, Wei Li, Qing Jiang, Yuan Lu, Xiaoya Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Univ Sci & Technol Beijing Key Lab Ind Proc Knowledge Automat Minist Educ Beijing 100083 Peoples R China
This study is aimed at addressing the problem of optimizing microgrid operations to improve local renewable energy consumption and ensure the stability of multi-energy systems. Microgrids are localized power systems t... 详细信息
来源: 评论
Tracking interval control for urban rail trains based on safe reinforcement learning
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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 第PartB期137卷
作者: Lin, Junting Qiu, Xiaohui Li, Maolin Lanzhou Jiaotong Univ Sch Automat & Elect Engn Lanzhou 730070 Peoples R China
In order to solve the problem of controlling the interval between trains in the new train control system, which aims to ensure the safe operation of trains and improve traffic density, the process of managing train sp... 详细信息
来源: 评论