The invention discloses a POI-based double-layer graph convolutional network traffic prediction method, which obtains a traffic flow predicted value by processing historical traffic flow data, and comprises the following steps of: constructing a model for a flow node function based on a POI; obtaining a function similarity matrix between the nodes based on the constructed model; nodes with similar functions are clustered, and a regional network is constructed; extracting spatial features on the nodes and the local area network respectively; and fusing the nodes and the spatial features extracted from the regional network, and outputting a prediction result of the traffic flow. The POI-based double-layer graph convolutional network traffic prediction method disclosed by the invention is high in prediction precision.
本发明公开了一种基于POI的双层图卷积网络交通预测方法,通过对历史交通流量数据进行处理,获得交通流量预测值,包括以下步骤:基于POI对流量节点功能构建模型;基于构建的模型获得节点之间的功能相似度矩阵;将具有相似功能的节点聚类,构建区域网络;在节点和区域网络上分别提取空间特征;将节点和区域网络上提取的空间特征融合,输出对交通流量的预测结果。本发明公开的基于POI的双层图卷积网络交通预测方法,预测精度高。
POI-based double-layer graph convolutional network traffic prediction method
基于POI的双层图卷积网络交通预测方法
2023-10-10
Patent
Electronic Resource
Chinese
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 |
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