The invention discloses a traffic flow prediction method and device based on a dynamic ordinary differential graph neural network, and the method employs a single encoder architecture, and system modules comprise a road traffic network semantic matrix building module, a spatial dependence capturing module, a time dependence extraction module, a dynamic graph ordinary differential network module, and a graph convolutional neural network module. A feature fusion gating unit, a traffic flow prediction module and a terminal design module. In order to solve the problem of Over-Smoothing of graph neural network node data in a traditional traffic flow prediction method, a dynamic graph ordinary differential network is introduced, an analytical solution of a road traffic network topology structure is abstracted by using an ordinary differential equation, spatial-temporal features are extracted by constructing a spatial-temporal attention module, and the spatial-temporal features are extracted by using a spatial-temporal attention module. And a feature fusion gating unit is used to further capture road traffic flow spatio-temporal data features, so that the traffic flow prediction precision is improved.

    本发明公开了基于动态常微分图神经网络的交通流量预测方法及装置,本发明方法使用单编码器架构,系统模块包括:建立道路交通网络语义矩阵模块,空间依赖捕捉模块,时间依赖提取模块,动态图常微分网络模块,图卷积神经网络模块,特征融合门控单元,交通流量预测模块和终端设计模块。本发明为解决传统交通流量预测方法中图神经网络节点数据相似(Over‑Smoothing)问题,引入动态图常微分网络,使用常微分方程抽象出道路交通网络拓扑结构的解析解,通过构建时空注意力模块提取时空特征,并使用特征融合门控单元进一步捕捉道路交通流时空数据特征,从而提升交通流量预测精度。


    Access

    Download


    Export, share and cite



    Title :

    Traffic flow prediction method and device based on dynamic ordinary differential graph neural network


    Additional title:

    基于动态常微分图神经网络的交通流量预测方法及装置


    Contributors:
    DU SHENGDONG (author) / YANG TAO (author) / HU JIE (author) / SU MIN (author) / YE XIANYAO (author)

    Publication date :

    2024-03-29


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES



    Traffic flow prediction method based on dynamic graph neural network

    XU GUANGXIA / HU XINTING / CHEN LANG et al. | European Patent Office | 2022

    Free access

    Traffic flow prediction method based on graph neural network

    PENG LAIHU / WU BAOWEN / QI YUBAO et al. | European Patent Office | 2024

    Free access

    Traffic flow real-time prediction method and device based on dynamic graph neural network

    REN XIANGSHENG / CEN YUKUO | European Patent Office | 2023

    Free access

    Traffic flow prediction method based on dynamic adaptive adversarial graph convolutional neural network

    WANG HUI / WANG YU / DU KAI | European Patent Office | 2024

    Free access

    Airport traffic flow prediction method based on graph neural network

    YAN ZHEN / YANG HONGYU / WU XIPING et al. | European Patent Office | 2023

    Free access