The invention discloses a traffic flow prediction method based on an attention mechanism, and solves the problem of low traffic flow prediction accuracy in the prior art. The method comprises the following steps: acquiring input data; obtaining a spatial similarity matrix, a time similarity matrix, a positive spatial relation matrix, a negative spatial relation matrix, a positive time relation matrix and a negative time relation matrix based on the input data; positive space similar attention, negative space similar attention, positive time similar attention and negative time similar attention are determined; determining a combined spatiotemporal attention based on the plurality of attention; extracting spatial features and time features based on the combined space-time attention; and carrying out feature fusion on the spatial features and the time features to obtain fused spatial and temporal features, and predicting the traffic flow of the target road based on the fused spatial and temporal features.

    本发明公开了一种基于注意力机制的交通流量预测方法,解决现有交通流量预测准确性低的问题。所述方法包括:获取输入数据;基于所述输入数据获取空间相似度矩阵、时间相似度矩阵、正向空间关系矩阵、负向空间关系矩阵、正向时间关系矩阵和负向时间关系矩阵;确定正向空间相似注意力、负向空间相似注意力、正向时间相似注意力和负向时间相似注意力;基于多个注意力确定组合时空注意力;基于所述组合时空注意力,提取空间特征和时间特征;对所述空间特征和所述时间特征进行特征融合,获得融合后时空特征,基于所述融合后时空特征预测目标道路的交通流量。


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    Title :

    Traffic flow prediction method based on attention mechanism


    Additional title:

    一种基于注意力机制的交通流量预测方法


    Contributors:
    SUN LIJUN (author) / LIU MINGZHI (author) / LIU GUANFENG (author) / YU XU (author)

    Publication date :

    2022-07-29


    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 / G06K Erkennen von Daten , RECOGNITION OF DATA / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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