The invention provides a traffic prediction method based on a double-dynamic graph attention network, and belongs to the technical field of traffic prediction methods. The method comprises the following steps: adding spatio-temporal information to an input traffic signal, generating a dynamic graph adjacency matrix through linear transformation, and performing dual transformation on a dynamic graph to generate a dual dynamic hypergraph adjacency matrix; inputting a traffic signal to be predicted and the double-dynamic graph adjacency matrix into a spatial feature extraction module, and capturing and integrating spatial correlation features; a time feature extraction module is used to capture time-related features on different time scales through a plurality of stacked gating attention linear units, and time-space related features captured by the current time-space feature extraction module are obtained; and the output module carries out linear processing and residual decomposition on the extracted spatio-temporal correlation features to obtain a prediction result of the current module and signal input of the next block, and integrates output of all spatio-temporal feature extraction modules to obtain a final prediction value. According to the method, a space-time convolutional network architecture is adopted to learn dynamic characteristics in traffic signals, and the traffic prediction precision is improved.

    本发明提供一种基于双动态图注意力网络的交通预测方法,属于交通预测方法的技术领域。本发明方法,包括以下步骤:对输入的交通信号附加时空信息并通过线性变换生成动态图邻接矩阵,同时对动态图对偶变换生成对偶动态超图邻接矩阵;将待预测的交通信号和双动态图邻接矩阵输入到空间特征提取模块,捕获并整合空间相关特征;使用时间特征提取模块,通过堆叠的多个门控注意力线性单元在不同时间尺度上捕获时间相关特征,获取到当前时空特征提取模块捕获的时空相关特征;输出模块对提取到的时空相关特征进行线性处理和残差分解,得到当前模块的预测结果和下一块的信号输入,整合所有时空特征提取模块输出得到最终预测值。本发明方法采用时空卷积网络架构来学习交通信号中的动态特性,提高交通预测精度。


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    Titel :

    Traffic prediction method based on double-dynamic graph attention network


    Weitere Titelangaben:

    一种基于双动态图注意力网络的交通预测方法


    Beteiligte:
    ZHAI HUAWEI (Autor:in) / YUAN XIAODONG (Autor:in) / CUI LICHENG (Autor:in) / ZHANG ZIJIAN (Autor:in) / CAO YIFAN (Autor:in) / YANG WENCHAO (Autor:in)

    Erscheinungsdatum :

    30.05.2025


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    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 / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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