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FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction Conference paper
Yang, Linghua, Chen, Wantong, He, Xiaoxi, Wei, Shuyue, Xu, Yi, Zhou, Zimu, Tong, Yongxin. FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction[C], New York, NY, USA:Association for Computing Machinery, 2024, 6105–6116.
Authors:  Yang, Linghua;  Chen, Wantong;  He, Xiaoxi;  Wei, Shuyue;  Xu, Yi; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/09/11
Federated Learning  Traffic Prediction  Spatial-temporal Graph Neural Network  
Cross-City Multi-Granular Adaptive Transfer Learning for Traffic Flow Prediction Journal article
Mo, Jiqian, Gong, Zhiguo. Cross-City Multi-Granular Adaptive Transfer Learning for Traffic Flow Prediction[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(11), 11246-11258.
Authors:  Mo, Jiqian;  Gong, Zhiguo
Favorite | TC[WOS]:6 TC[Scopus]:4  IF:8.9/8.8 | Submit date：2023/12/04
Attention  Meta-learning  Traffic Flow Prediction  Transfer Learning  
Multi-view dynamic graph convolution neural network for traffic flow prediction Journal article
Huang,Xiaohui, Ye,Yuming, Yang,Xiaofei, Xiong,Liyan. Multi-view dynamic graph convolution neural network for traffic flow prediction[J]. Expert Systems with Applications, 2023, 222, 119779.
Authors:  Huang,Xiaohui;  Ye,Yuming;  Yang,Xiaofei;  Xiong,Liyan
Favorite | TC[WOS]:25 TC[Scopus]:27  IF:7.5/7.6 | Submit date：2023/08/03
Dynamic Fusion  Graph Convolution Network  Multi-view Encoder–decoders  Traffic Flow Prediction  
A multi-mode traffic flow prediction method with clustering based attention convolution LSTM Journal article
Huang, Xiaohui, Ye, Yuming, Wang, Cheng, Yang, Xiaofei, Xiong, Liyan. A multi-mode traffic flow prediction method with clustering based attention convolution LSTM[J]. Applied Intelligence, 2022, 52(13), 14773-14786.
Authors:  Huang, Xiaohui;  Ye, Yuming;  Wang, Cheng;  Yang, Xiaofei;  Xiong, Liyan
Favorite | TC[WOS]:3 TC[Scopus]:10  IF:3.4/3.9 | Submit date：2022/05/13
Attention Mechanism  Encoder-decoder  Multi-mode  Spatial-temporal Data  Traffic Flow Prediction  
Multi-mode dynamic residual graph convolution network for traffic flow prediction Journal article
Huang, Xiaohui, Ye, Yuming, Ding, Weihua, Yang, Xiaofei, Xiong, Liyan. Multi-mode dynamic residual graph convolution network for traffic flow prediction[J]. INFORMATION SCIENCES, 2022, 609, 548-564.
Authors:  Huang, Xiaohui;  Ye, Yuming;  Ding, Weihua;  Yang, Xiaofei;  Xiong, Liyan
Favorite | TC[WOS]:22 TC[Scopus]:23  IF:0/0 | Submit date：2022/08/02
Graph Convolution Network  Multi-mode Fusion  Spatio-temporal Data  Traffic Flow Prediction  
Adaptive traffic signal management method combining deep learning and simulation Journal article
Mok, Kawai, Zhang, Liming. Adaptive traffic signal management method combining deep learning and simulation[J]. Multimedia Tools and Applications, 2022, 83(5), 15439-15459.
Authors:  Mok, Kawai;  Zhang, Liming
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:3.0/2.9 | Submit date：2022/08/05
Deep Learning Based Vehicle Detection  Adaptive Traffic Signal Management  Traffic Data Acquisition  Traffic Flow Prediction  
Vehicle Trajectory Prediction in Connected Environments via Heterogeneous Context-Aware Graph Convolutional Networks Journal article
Lu, Yuhuan, Wang, Wei, Hu, Xiping, Xu, Pengpeng, Zhou, Shengwei, Cai, Ming. Vehicle Trajectory Prediction in Connected Environments via Heterogeneous Context-Aware Graph Convolutional Networks[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 24(8), 8452 - 8464.
Authors:  Lu, Yuhuan;  Wang, Wei;  Hu, Xiping;  Xu, Pengpeng;  Zhou, Shengwei; et al.
Favorite | TC[WOS]:26 TC[Scopus]:26  IF:7.9/8.3 | Submit date：2022/08/05
Trajectory  Vehicle Dynamics  Predictive Models  Convolutional Neural Networks  Roads  Feature Extraction  Dynamics  Traffic Big Data  Graph Neural Networks  Trajectory Prediction  Connected Vehicles  Interaction Context  
Multi-step Coupled Graph Convolution with Temporal-Attention for Traffic Flow Prediction Journal article
Huang, Xiaohui, Ye, Yuming, Yang, Xiaofei, Xiong, Liyan. Multi-step Coupled Graph Convolution with Temporal-Attention for Traffic Flow Prediction[J]. IEEE Access, 2022, 10, 48179-48192.
Authors:  Huang, Xiaohui;  Ye, Yuming;  Yang, Xiaofei;  Xiong, Liyan
Favorite | TC[WOS]:5 TC[Scopus]:7  IF:3.4/3.7 | Submit date：2022/05/17
Graph Convolutional Network  Multi-step Attention  Traffic Flow Prediction  
A time-dependent attention convolutional LSTM method for traffic flow prediction Journal article
Xiaohui Huang, Jie Tang, Xiaofei Yang, Liyan Xiong. A time-dependent attention convolutional LSTM method for traffic flow prediction[J]. APPLIED INTELLIGENCE, 2022, 52(15), 17371–17386.
Authors:  Xiaohui Huang;  Jie Tang;  Xiaofei Yang;  Liyan Xiong
Favorite | TC[WOS]:10 TC[Scopus]:11  IF:3.4/3.9 | Submit date：2022/05/17
Attention Mechanism  Convolutional Lstm  Spatio-temporal Data  Traffic Flow Prediction  
Multi-feature Urban Traffic Prediction Based on Unconstrained Graph Attention Network Conference paper
Hangtao He, Kejiang Ye, Cheng-Zhong Xu. Multi-feature Urban Traffic Prediction Based on Unconstrained Graph Attention Network[C]:IEEE, 2021, 1409-1417.
Authors:  Hangtao He;  Kejiang Ye;  Cheng-Zhong Xu
Favorite | TC[WOS]:6 TC[Scopus]:8 | Submit date：2022/05/13
Traffic Prediction  Graph Neural Networks  Interpretability