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CASIA OpenIR
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Parallel Transportation in TransVerse: From Foundation Models to DeCAST 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 卷号: 24, 期号: 12, 页码: 15310-15327
作者:  Zhao, Chen;  Wang, Xiao;  Lv, Yisheng;  Tian, Yonglin;  Lin, Yilun;  Wang, Fei-Yue
Adobe PDF(4139Kb)  |  收藏  |  浏览/下载：166/6  |  提交时间：2023/11/16
Intelligent Transportation Systems (ITS)  Cyber-Physical-Social Systems (CPSS)  Artificial Systems, Computational Experiments, Parallel Execution (ACP)  Decentralized/Distributed Autonomous Operations and Organizations (DAO)  
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：128/61  |  提交时间：2023/08/10
High-speed railway  reinforcement learning  train timetable rescheduling  Transformer  
Traffic Signal Timing via Deep Reinforcement Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2016, 期号: 3, 页码: 247-254
作者:  Li Li;  Lv YS(吕宜生);  Fei-Yue Wang
Adobe PDF(509Kb)  |  收藏  |  浏览/下载：78/38  |  提交时间：2022/04/08
Traffic control , reinforcement learning , deep learning , deep reinforcement learning  
On Iterative Proportional Updating: Limitations and Improvements for General Population Synthesis 期刊论文
IEEE Transactions on Cybernetics, 2022, 卷号: 52, 期号: 3, 页码: 1726-1735
作者:  Peijun Ye;  Bin Tian;  Yisheng Lv;  Qijie Li;  Fei-Yue Wang
Adobe PDF(1066Kb)  |  收藏  |  浏览/下载：228/49  |  提交时间：2020/10/15
Agent-based simulation, bilevel optimization, iterative proportional updating (IPU), population synthesis  
Traffic Flow Prediction With Big Data: A Deep Learning Approach 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2015, 卷号: 16, 期号: 2, 页码: 865-873
作者:  Lv, Yisheng;  Duan, Yanjie;  Kang, Wenwen;  Li, Zhengxi;  Wang, Fei-Yue
浏览  |  Adobe PDF(1520Kb)  |  收藏  |  浏览/下载：3826/2345  |  提交时间：2015/09/21
Deep Learning  Stacked Autoencoders (Saes)  Traffic Flow Prediction