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CASIA OpenIR
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HMDRL: Hierarchical Mixed Deep Reinforcement Learning to Balance Vehicle Supply and Demand 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 12
作者:  Xi, Jinhao;  Zhu, Fenghua;  Ye, Peijun;  Lv, Yisheng;  Tang, Haina;  Wang, Fei-Yue
Adobe PDF(3316Kb)  |  收藏  |  浏览/下载：260/30  |  提交时间：2022/09/19
deep reinforcement learning  online ride-hailing system  hierarchical repositioning framework  parallel coordination mechanism  mixed state  
AdapGL: An adaptive graph learning algorithm for traffic prediction based on spatiotemporal neural networks 期刊论文
Transportation Research Part C, 2022, 期号: 99, 页码: 1-1
作者:  Wei Zhang;  Fenghua Zhu;  Yisheng Lv;  Chang Tan;  Wen Liu;  Xin Zhang;  Fei-Yue Wang
Adobe PDF(2619Kb)  |  收藏  |  浏览/下载：366/123  |  提交时间：2022/04/08
Adaptive graph learning, Traffic prediction, Graph convolutional network, Expectation maximization, Deep learning  
A Semi-supervised End-to-end Framework for Transportation Mode Detection by Using GPS-enabled Sensing Devices 期刊论文
IEEE Internet of Things Journal, 2022, 卷号: 9, 期号: 10, 页码: 7842-7852
作者:  Zhishuai Li;  Gang Xiong;  Zebing Wei;  YIsheng Lv;  Noreen Anwar;  Fei-Yue Wang
Adobe PDF(2754Kb)  |  收藏  |  浏览/下载：214/64  |  提交时间：2022/04/08
Transportation mode detection , Semi-supervised learning, Human mobility , GPS trajectory.  
FII-CenterNet: An Anchor-Free Detector With Foreground Attention for Traffic Object Detection 期刊论文
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 卷号: 70, 期号: 1, 页码: 121-132
作者:  Fan, Siqi;  Zhu, Fenghua;  Chen, Shichao;  Zhang, Hui;  Tian, Bin;  Lv, Yisheng;  Wang, Fei-Yue
Adobe PDF(7159Kb)  |  收藏  |  浏览/下载：243/36  |  提交时间：2021/03/29
Object detection  Anchor-free detector  Foreground region proposal  
Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 卷号: 21, 期号: 4, 页码: 1624-1630
作者:  Chen, Yuanyuan;  Lv, Yisheng;  Wang, Fei-Yue
浏览  |  Adobe PDF(2070Kb)  |  收藏  |  浏览/下载：362/65  |  提交时间：2020/06/02
Generators  Data models  Gallium nitride  Generative adversarial networks  Training  Loss measurement  Biological system modeling  Parallel data  generative adversarial networks  traffic flow imputation  data augmentation  deep learning  
Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 21, 期号: 10, 页码: 4063 - 4071
作者:  Fenghua Zhu;  Yisheng Lv;  Yuanyuan Chen;  Xiao Wang;  Gang Xiong;  Fei-Yue Wang
浏览  |  Adobe PDF(2879Kb)  |  收藏  |  浏览/下载：444/227  |  提交时间：2020/10/15
Intelligent transportation systems  
On Iterative Proportional Updating: Limitations and Improvements for General Population Synthesis 期刊论文
IEEE Transactions on Cybernetics, 2020, 卷号: 99, 期号: 1, 页码: 1-10
作者:  Peijun Ye;  Bin Tian;  Yisheng Lv;  Qijie Li;  Fei-Yue Wang
Adobe PDF(1310Kb)  |  收藏  |  浏览/下载：161/42  |  提交时间：2020/10/15
Agent-based simulation, bilevel optimization, iterative proportional updating (IPU), population synthesis  
Acting As A Decision Maker: Traffic-Condition-Aware Ensemble Learning for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 期号: Accepted, 页码: Accepted
作者:  Yuanyuan Chen;  Hongyu Chen;  Peijun Ye;  Yisheng Lv;  Fei-Yue Wang
Adobe PDF(2382Kb)  |  收藏  |  浏览/下载：271/57  |  提交时间：2020/10/16
Traffic Flow Prediction  Ensemble Learning  Deep Learning  
Detecting Traffic Information From Social Media Texts With Deep Learning Approaches 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 卷号: 20, 期号: 8, 页码: 3049-3058
作者:  Chen, Yuanyuan;  Lv, Yisheng;  Wang, Xiao;  Li, Lingxi;  Wang, Fei-Yue
Adobe PDF(2273Kb)  |  收藏  |  浏览/下载：423/106  |  提交时间：2019/08/28
Deep learning  social transportation  traffic information detection  social media  text mining  
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：73/36  |  提交时间：2022/04/08
Traffic control , reinforcement learning , deep learning , deep reinforcement learning