The invention relates to a traffic flow space-time prediction method based on a graph neural network, and the method comprises the following steps: firstly, inputting traffic flow data to a full connection layer, and enabling the full connection layer to convert a feature dimension into a specified dimension; then, spatial features and time features of the traffic flow data are extracted respectively through a parallel graph convolution enhanced transformer module and a time feature extraction module; and finally, fusing the spatial features and the time features in a space-time mixing layer, and converting the fused features to a specified output dimension through a full connection layer to obtain a final traffic flow prediction result. Compared with the prior art, the method has the advantages of accurate prediction, low prediction complexity, high efficiency and the like.
本发明涉及一种基于图神经网络的交通流时空预测方法,该方法包括以下步骤:首先,输入交通流数据到全连接层,全连接层将特征维度转换到指定维度;然后,通过并行的图卷积增强的transformer模块和时间特征提取模块分别提取交通流数据的空间特征和时间特征;最后,在时空混合层里将空间特征与时间特征进行融合,并经过全连接层转换到指定的输出维度得到最终的交通流预测结果。与现有技术相比,本发明具有预测准确、预测复杂度低和高效等优点。
Traffic flow space-time prediction method based on graph neural network
一种基于图神经网络的交通流时空预测方法
2024-07-02
Patent
Electronic Resource
Chinese
IPC: | 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 / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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