Multi-mode dynamic residual graph convolution network for traffic flow prediction

被引：0
|
作者：
Huang, Xiaohui [1 ]
Ye, Yuming [1 ]
Ding, Weihua [1 ]
Yang, Xiaofei [2 ]
Xiong, Liyan [1 ]
机构：
[1] Department of Information Engineering, East China Jiaotong University, Jiangxi, China
[2] Faculty of Science and Technology, University of Macau, Macau, China
来源：
Information Sciences | 2022年 / 609卷
基金：
中国国家自然科学基金;
关键词：
Dynamic graph - Graph convolution network - Mode dynamics - Multi-mode fusion - Multimodes - Spatio-temporal data - Traffic flow - Traffic flow prediction - Urban development - Urban traffic congestion;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：548 / 564
相关论文
共 50 条
  • [21] Traffic Flow Prediction Based on Multi-Mode Spatial-Temporal Convolution of Mixed Hop Diffuse ODE
    Huang, Xiaohui
    Lan, Yuanchun
    Ye, Yuming
    Wang, Junyang
    Jiang, Yuan
    ELECTRONICS, 2022, 11 (19)
  • [22] An improved dynamic Chebyshev graph convolution network for traffic flow prediction with spatial-temporal attention
    Lyuchao Liao
    Zhiyuan Hu
    Yuxin Zheng
    Shuoben Bi
    Fumin Zou
    Huai Qiu
    Maolin Zhang
    Applied Intelligence, 2022, 52 : 16104 - 16116
  • [23] TSHDNet: temporal-spatial heterogeneity decoupling network for multi-mode traffic flow prediction
    Wu, Mei
    Weng, Wenchao
    Wang, Xinran
    Seng, Dewen
    APPLIED INTELLIGENCE, 2025, 55 (04)
  • [24] An improved dynamic Chebyshev graph convolution network for traffic flow prediction with spatial-temporal attention
    Liao, Lyuchao
    Hu, Zhiyuan
    Zheng, Yuxin
    Bi, Shuoben
    Zou, Fumin
    Qiu, Huai
    Zhang, Maolin
    APPLIED INTELLIGENCE, 2022, 52 (14) : 16104 - 16116
  • [25] A period-extracted multi-featured dynamic graph convolution network for traffic demand prediction
    Zhu, Yuntian
    Ni, Qingjian
    APPLIED INTELLIGENCE, 2024, 54 (01) : 722 - 737
  • [26] A period-extracted multi-featured dynamic graph convolution network for traffic demand prediction
    Yuntian Zhu
    Qingjian Ni
    Applied Intelligence, 2024, 54 : 722 - 737
  • [27] A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility
    Jiahao Ling
    Yuanchun Lan
    Xiaohui Huang
    Xiaofei Yang
    Complex & Intelligent Systems, 2024, 10 : 3305 - 3317
  • [28] A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility
    Ling, Jiahao
    Lan, Yuanchun
    Huang, Xiaohui
    Yang, Xiaofei
    COMPLEX & INTELLIGENT SYSTEMS, 2024, 10 (03) : 3305 - 3317
  • [29] Multi-scale Fusion Dynamic Graph Neural Network for Traffic Flow Prediction
    Weng, Wenchao
    Chen, Qikai
    Dai, Yu
    Chen, Jingyang
    Chen, Dongliang
    ACM International Conference Proceeding Series, 2023, : 85 - 90
  • [30] Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction
    Sun, Yanfeng
    Jiang, Xiangheng
    Hu, Yongli
    Duan, Fuqing
    Guo, Kan
    Wang, Boyue
    Gao, Junbin
    Yin, Baocai
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (12) : 23680 - 23693
12345