The invention discloses a multi-feature fusion space-time attention graph convolutional neural network for traffic flow prediction. The multi-feature fusion space-time attention graph convolutional neural network is designed from three aspects of data processing, spatial correlation and temporal correlation. The method comprises the following steps: firstly, fusing obtained historical traffic flow data with external feature factors, and obtaining multi-feature fused space-time traffic data as a training sample; secondly, capturing a topological structure of an urban road network by using an attention map convolutional network, and obtaining traffic flow spatial features with multi-feature fusion; thirdly, inputting the obtained time sequence with the spatial features into a time feature extraction model formed by combining a gating circulation unit and an attention unit to capture the time features; and finally, comparing an output predicted value with an actual value, and changing related parameters until the model is optimized.

    本发明公开了一种用于交通流预测的多特征融合的时空注意图卷积神经网络,从数据处理、空间相关性、时间相关性三个角度出发设计。首先,对获取到的历史交通流数据与外部特征因素融合,获取多特征融合的时空交通数据作为训练样本;其次,利用注意图卷积网络捕获城市道路网络的拓扑结构,获得多特征融合的交通流空间特征;接着,将获得的具有空间特征的时间序列输入到由门控循环单元和注意力单元相结合的时间特征提取模型中捕捉时间特征;最后,将输出的预测值与实际值相对比,更改相关参数直至模型最优化。


    Access

    Download


    Export, share and cite



    Title :

    Traffic flow prediction method of space-time attention graph convolutional network based on multi-feature fusion


    Additional title:

    一种基于多特征融合的时空注意图卷积网络的交通流预测方法


    Contributors:
    CHEN YAJUN (author) / DING ZHIMING (author) / GUO LIMIN (author)

    Publication date :

    2023-05-26


    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 / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / 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



    Multi-view fusion space-time dynamic graph convolutional network urban traffic flow prediction method

    YUAN GUAN / ZHAO WENZHU / ZHANG YANMEI et al. | European Patent Office | 2023

    Free access

    Traffic flow prediction method based on dynamic multi-view space-time fusion graph convolutional network

    SHI QUAN / CAO CHENYANG / BAO YINXIN et al. | European Patent Office | 2025

    Free access

    Traffic flow prediction method and system of attention time-space synchronization graph convolutional network

    XIA DAWEN / WEI XIAODUO / LI HUAQING et al. | European Patent Office | 2023

    Free access

    Traffic flow prediction method based on time attention circulation graph convolutional neural network

    FAN WENDONG / SHU MIN / SONG YUN et al. | European Patent Office | 2023

    Free access

    Space-time ARMA graph convolutional network traffic flow prediction method

    CAO YANG / XIAO PEICHENG / SHEN QINQIN et al. | European Patent Office | 2024

    Free access