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CASIA OpenIR
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Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing 期刊论文
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 页码: 1-15
作者:  Jing Yang;  Yutong Wang;  Xingxia Wang;  Xiaoxing Wang;  Xiao Wang;  Fei-Yue Wang
Adobe PDF(3887Kb)  |  收藏  |  浏览/下载：58/14  |  提交时间：2024/06/06
The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0 期刊论文
Information Fusion, 2024, 卷号: 107, 页码: 1-16
作者:  Xiao Wang;  Yutong Wang;  Jing Yang;  Xiaofeng Jia;  Lijun Li;  Weiping Ding;  Fei-Yue Wang
Adobe PDF(4446Kb)  |  收藏  |  浏览/下载：58/11  |  提交时间：2024/06/06
Multi-source data fusion  CPSS  Industrial metaverses  Parallel manufacturing  Social manufacturing  
Computational Experiments for Complex Social Systems: Integrated Design of Experiment System 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1175-1189
作者:  Xiao Xue;  Xiangning Yu;  Deyu Zhou;  Xiao Wang;  Chongke Bi;  Shufang Wang;  Fei-Yue Wang
Adobe PDF(11890Kb)  |  收藏  |  浏览/下载：78/12  |  提交时间：2024/04/10
Artificial society  computational experiments  model integration  operation engine  technology integration  
Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1822-1833
作者:  Wei Xu;  Chen Zhao;  Jie Cheng;  Yin Wang;  Yiqing Tang;  Tao Zhang;  Zhiming Yuan;  Yisheng Lv;  Fei-Yue Wang
Adobe PDF(3484Kb)  |  收藏  |  浏览/下载：152/69  |  提交时间：2023/08/10
High-speed railway  reinforcement learning  train timetable rescheduling  Transformer  
Parallel reinforcement learning: a framework and case study 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2018, 卷号: 5, 期号: 4, 页码: 827-835
作者:  Teng Liu;  Bin TIan;  Yunfeng Ai;  Li Li;  Dongpu Cao;  Feiyue Wang
Adobe PDF(7005Kb)  |  收藏  |  浏览/下载：75/19  |  提交时间：2023/05/05
The Development of AgriVerse: Past, Present, and Future 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 页码: 10
作者:  Kang, Mengzhen;  Wang, Xiujuan;  Wang, Haoyu;  Hua, Jing;  de Reffye, Philippe;  Wang, Fei-Yue
Adobe PDF(4290Kb)  |  收藏  |  浏览/下载：342/89  |  提交时间：2023/02/22
Computational modeling  Biological systems  Biomass  Biological system modeling  Production  Plants (biology)  Metaverse  Agricultural metaverse (AgriVerse)  agriculture cyber-physical-social system (CPSS)  artificial systems  computational experiments  and parallel execution (ACP)  decentralized science (DeSci)  knowledge-and-data driven modeling  parallel agriculture  plant model  
The Metaverse of Mind: Perspectives on DeSci for DeEco and DeSoc 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 12, 页码: 2043-2046
作者:  Fei-Yue Wang
Adobe PDF(101Kb)  |  收藏  |  浏览/下载：142/48  |  提交时间：2022/12/02
HMDRL: Hierarchical Mixed Deep Reinforcement Learning to Balance Vehicle Supply and Demand 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 卷号: 23, 期号: 11, 页码: 21861-21872
作者:  Xi, Jinhao;  Zhu, Fenghua;  Ye, Peijun;  Lv, Yisheng;  Tang, Haina;  Wang, Fei-Yue
Adobe PDF(3316Kb)  |  收藏  |  浏览/下载：335/46  |  提交时间：2022/09/19
deep reinforcement learning  online ride-hailing system  hierarchical repositioning framework  parallel coordination mechanism  mixed state  
Supervised assisted deep reinforcement learning for emergency voltage control of power systems 期刊论文
NEUROCOMPUTING, 2022, 卷号: 475, 页码: 69-79
作者:  Li, Xiaoshuang;  Wang, Xiao;  Zheng, Xinhu;  Dai, Yuxin;  Yu, Zhihong;  Zhang, Jun Jason;  Bu, Guangquan;  Wang, Fei-Yue
Adobe PDF(2551Kb)  |  收藏  |  浏览/下载：368/78  |  提交时间：2022/06/06
Deep reinforcement learning  Behavioral cloning  Dynamic demonstration  Emergency control  
SADRL: Merging human experience with machine intelligence via supervised assisted deep reinforcement learning 期刊论文
NEUROCOMPUTING, 2022, 卷号: 467, 页码: 300-309
作者:  Li, Xiaoshuang;  Wang, Xiao;  Zheng, Xinhu;  Jin, Junchen;  Huang, Yanhao;  Zhang, Jun Jason;  Wang, Fei-Yue
Adobe PDF(1244Kb)  |  收藏  |  浏览/下载：356/81  |  提交时间：2021/12/28
Deep reinforcement learning  Behavioral cloning  Dynamic demonstration  Double DQN