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CASIA OpenIR
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A Multi-Stream Feature Fusion Approach for Traffic Prediction 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2022, 卷号: 23, 期号: 2, 页码: 1456-1466
作者:  Zhishuai Li;  Gang Xiong;  Yonglin Tian;  Yisheng Lv;  Yuanyuan Chen;  Pan Hui;  Xiang Su
Adobe PDF(3248Kb)  |  收藏  |  浏览/下载：347/62  |  提交时间：2020/10/15
Traffic prediction, graph convolutional neural network, deep learning, multi-stream  
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：349/115  |  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：202/59  |  提交时间：2022/04/08
Transportation mode detection , Semi-supervised learning, Human mobility , GPS trajectory.  
MLRNN: Taxi Demand Prediction Based on Multi-Level Deep Learning and Regional Heterogeneity Analysis 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Chizhan Zhang;  Fenghua Zhu;  Yisheng Lv;  Peijun Ye;  Feiyue Wang
Adobe PDF(4431Kb)  |  收藏  |  浏览/下载：205/46  |  提交时间：2021/06/16
Taxi demand prediction  taxi zone clustering  heterogeneity analysis  deep learning  
Trip Purposes Mining From Mobile Signaling Data 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 99, 期号: 99, 页码: 13
作者:  Li, Zhishuai;  Xiong, Gang;  Wei, Zebing;  Zhang, Yu;  Zheng, Meng;  Liu, Xiaoli;  Tarkoma, Sasu;  Huang, Min;  Lv, Yisheng;  Wu, Chuheng
Adobe PDF(3962Kb)  |  收藏  |  浏览/下载：324/68  |  提交时间：2022/01/27
Cellular networks  Trajectory  Semantics  Unsupervised learning  Supervised learning  Resource management  Public transportation  Trip purpose inference  cellular network data  latent Dirichlet allocation  travel behavior  big data  
Taxi Demand Prediction Using Parallel Multi-Task Learning Model 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 99, 期号: 1, 页码: 1-10
作者:  Chizhan Zhang;  Fenghua Zhu;  Xiao Wang;  Leilei Sun;  Haina Tang;  Yisheng Lv
浏览  |  Adobe PDF(3947Kb)  |  收藏  |  浏览/下载：194/79  |  提交时间：2020/10/15
Taxi demand prediction, pick-up/drop-off demand, multi-task learning, LSTM, 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：413/221  |  提交时间：2020/10/15
Intelligent transportation systems  
Discover Trip Purposes from Cellular Network Data with Topic Modelling 期刊论文
IEEE Intelligent Transportation Systems Magazine, 2020, 卷号: 99, 期号: 1, 页码: 0-0
作者:  Xueliang Zhao;  Zhishuai Li;  Discover Trip Purposes from Cellular Network Data with Topic Modelling;  Yisheng Lv
浏览  |  Adobe PDF(2244Kb)  |  收藏  |  浏览/下载：199/57  |  提交时间：2020/10/15
trip purpose  
A Hybrid Deep Learning Approach with GCN and LSTM for Traffic Flow Prediction 会议论文
, Auckland, New Zealand, 2019-10-27
作者:  Zhishuai Li;  Gang Xiong;  Yuanyuan Chen;  Yisheng Lv;  Bin Hu;  Fenghua Zhu;  Fei-Yue Wang
Adobe PDF(305Kb)  |  收藏  |  浏览/下载：279/59  |  提交时间：2020/10/15
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
浏览  |  Adobe PDF(2273Kb)  |  收藏  |  浏览/下载：393/102  |  提交时间：2019/08/28
Deep learning  social transportation  traffic information detection  social media  text mining