The invention provides a traffic flow prediction method based on a dynamic multi-graph hybrid expert graph neural network. The method can perform feature extraction and flow prediction for different road types and regional features. The method comprises the following steps: obtaining a road network map; obtaining respective traffic flow sequences of N road sections corresponding to the N nodes; for the road network map, constructing a distance-based map according to the distance correlation between every two road sections in the N road sections; obtaining respective attributes of the N road sections and semantic correlation between every two road sections in the N road sections, and constructing a graph based on a knowledge graph; and according to the distance-based graph, the knowledge graph-based graph and the respective traffic flow sequences of the N road sections, predicting respective estimated traffic flows of the N road sections at the next moment.
本公开提供了一种基于动态多图混合专家图神经网络的交通流量预测方法,所述方法能够针对不同道路类型和区域特征进行特征提取和流量预测。所述方法包括:获得路网图;获得所述N个节点对应的N个路段各自的交通流量序列;针对所述路网图,根据N个路段中每两个路段之间的距离相关性,构建基于距离的图;获得所述N个路段各自的属性以及N个路段中每两个路段之间的语义相关性,构建基于知识图谱的图;根据所述基于距离的图、所述基于知识图谱的图以及所述N个路段各自的交通流量序列,预测所述N个路段各自在下一时刻的预估交通流量。
Traffic flow prediction method based on dynamic multi-graph hybrid expert graph neural network
基于动态多图混合专家图神经网络的交通流量预测方法
2025-06-06
Patent
Electronic Resource
Chinese
IPC: | 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 / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung |
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