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Multi-level traffic-responsive tilt camera surveillance through predictive correlated online learning Journal article
Li, Tao, Bian, Zilin, Lei, Haozhe, Zuo, Fan, Yang, Ya Ting, Zhu, Quanyan, Li, Zhenning, Ozbay, Kaan. Multi-level traffic-responsive tilt camera surveillance through predictive correlated online learning[J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2024, 167, 104804.
Authors:  Li, Tao;  Bian, Zilin;  Lei, Haozhe;  Zuo, Fan;  Yang, Ya Ting; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:7.6/9.6 | Submit date：2024/09/03
Real-time Traffic Surveillance  Online Learning Control  Spatial–temporal Forecasting  Traffic State Estimation  Dynamic Route Planning  
A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility Journal article
Ling, Jiahao, Lan, Yuanchun, Huang, Xiaohui, Yang, Xiaofei. A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility[J]. Complex and Intelligent Systems, 2024, 10(3), 3305-3317.
Authors:  Ling, Jiahao;  Lan, Yuanchun;  Huang, Xiaohui;  Yang, Xiaofei
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:5.0/5.2 | Submit date：2024/05/16
Multivariate Time Series  Periodicity  Spatial–temporal  Traffic Forecasting  
A novel model for tourism demand forecasting with spatial–temporal feature enhancement and image-driven method Journal article
Dong, Yunxuan, Zhou, Binggui, Yang, Guanghua, Hou, Fen, Hu, Zheng, Ma, Shaodan. A novel model for tourism demand forecasting with spatial–temporal feature enhancement and image-driven method[J]. NEUROCOMPUTING, 2023, 556, 126663.
Authors:  Dong, Yunxuan;  Zhou, Binggui;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:4 TC[Scopus]:5  IF:5.5/5.5 | Submit date：2023/08/30
Deep Learning  Feature Enhancement  Spatial Series To Image Series  Spatial–temporal Learning  Tourism Demand Forecasting  
A graph-attention based spatial-temporal learning framework for tourism demand forecasting Journal article
Zhou, Binggui, Dong, Yunxuan, Yang, Guanghua, Hou, Fen, Hu, Zheng, Xu, Suxiu, Ma, Shaodan. A graph-attention based spatial-temporal learning framework for tourism demand forecasting[J]. Knowledge-Based Systems, 2023, 263, 110275.
Authors:  Zhou, Binggui;  Dong, Yunxuan;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:7 TC[Scopus]:8  IF:7.2/7.4 | Submit date：2023/04/03
Tourism Demand Forecasting  Dynamic Spatial Connections  Spatial-temporal Learning  Graph Neural Network  Attention Mechanism  
A Spatial-temporal Model for Tourism Demand Forecasting Conference paper
Dong, Yunxuan, Zhou, Binggui, Yang, Guanghua, Hou, Fen, Ma, Shaodan. A Spatial-temporal Model for Tourism Demand Forecasting[C], 2022, 1810-1814.
Authors:  Dong, Yunxuan;  Zhou, Binggui;  Yang, Guanghua;  Hou, Fen;  Ma, Shaodan
Favorite | TC[Scopus]:0 | Submit date：2022/08/05
Fully Connected Long Short Term Memory  Spatial-temporal Learning  Tourism Demand Forecasting  
ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting Conference paper
Tian,Kelang, Guo,Jingjie, Ye,Kejiang, Xu,Cheng Zhong. ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting[C], 2020, 714-721.
Authors:  Tian,Kelang;  Guo,Jingjie;  Ye,Kejiang;  Xu,Cheng Zhong
Favorite | TC[WOS]:8 TC[Scopus]:10 | Submit date：2021/03/09
Graph Convolutional Networks  Spatial-temporal Model  Traffic Forecasting  
Multi-STGCnet: A Graph Convolution Based Spatial-Temporal Framework for Subway Passenger Flow Forecasting Conference paper
Ye,Jiexia, Zhao,Juanjuan, Ye,Kejiang, Xu,Chengzhong. Multi-STGCnet: A Graph Convolution Based Spatial-Temporal Framework for Subway Passenger Flow Forecasting[C], 2020.
Authors:  Ye,Jiexia;  Zhao,Juanjuan;  Ye,Kejiang;  Xu,Chengzhong
Favorite | TC[WOS]:34 TC[Scopus]:34 | Submit date：2021/03/09
Gcn  Lstm  Passenger Flow Forecasting  Spatial-temporal Forecasting