The invention provides a traffic flow prediction method based on an adaptive generalized PageRank graph neural network. The method comprises the following steps: acquiring POI (Point of Information) information in public traffic flow data, and constructing a distance code; the time information is constructed into time codes, and the distance codes and the time codes are spliced into time-space codes DTE; constructing a time-space diagram neural network model based on the generalized PageRank, taking the historical time sequence feature H and the DTE as input data of the time-space diagram neural network model based on the generalized PageRank, training the time-space diagram neural network model based on the generalized PageRank, inputting the historical traffic flow sequence into the trained time-space diagram neural network model based on the generalized PageRank, and obtaining the time-space diagram neural network model based on the generalized PageRank. And outputting a future traffic flow sequence based on the time-space diagram neural network model of the generalized PageRank. According to the method, RPTA is designed to adaptively model nonlinear correlation between different time steps, distance and time codes are designed to combine geographic information and time information of the road network, and the traffic flow of the road can be effectively predicted.

    本发明提供了一种基于自适应广义PageRank图神经网络的交通流预测方法。该方法包括:获取公共交通流量数据中的信息点POI信息,构建距离编码;将时间信息构建为时间编码,拼接距离编码和时间编码为时空编码DTE;构建基于广义PageRank的时空图神经网络模型,将历史时间序列特征H和DTE作为基于广义PageRank的时空图神经网络模型的输入数据,对基于广义PageRank的时空图神经网络模型的进行训练,将历史交通流量序列输入到训练好的基于广义PageRank的时空图神经网络模型,基于广义PageRank的时空图神经网络模型输出未来交通流量序列。本发明设计了RPTA来自适应地建模不同时间步长之间的非线性相关性,设计了距离和时间编码来合并道路网络的地理信息和时间信息,可以有效地预测道路的交通流。


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    Titel :

    Traffic flow prediction method based on adaptive generalized PageRank graph neural network


    Weitere Titelangaben:

    一种基于自适应广义PageRank图神经网络的交通流预测方法


    Beteiligte:
    LU WEI (Autor:in) / KONG XIANGYUAN (Autor:in) / XING WEIWEI (Autor:in) / WEI XIANG (Autor:in) / ZHANG JIAN (Autor:in) / XING JINTAO (Autor:in)

    Erscheinungsdatum :

    2023-01-17


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    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



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