The invention belongs to the field of road traffic, and particularly relates to a high-speed station traffic flow prediction method of a hypergraph neural network fused with Transform. The method comprises the following steps: acquiring a dynamic directed graph structure between high-speed stations; constructing a directed hypergraph structure between the high-speed sites; extracting spatio-temporal features through the spatio-temporal blocks; and performing multi-step time sequence prediction by using the prediction block. By introducing the directed hypergraph structure and the attention mechanism, the dynamic time-space relationship in the complex road network can be better captured, so that the accuracy of traffic flow prediction is improved.
本发明属于道路交通领域,具体涉及一种融合Transformer的超图神经网络的高速站点车流量预测方法。本发明的方法包括:获取高速站点之间的动态有向图结构;构建高速站点之间有向超图结构;通过时空块提取时空特征;利用预测块进行多步时间序列预测。本发明通过引入有向超图结构和注意力机制,能够更好地捕捉复杂路网中的动态时空关系,从而提高交通流量预测的准确性。
Transform-fused hypergraph neural network-based high-speed station traffic flow prediction method
一种融合Transformer的超图神经网络的高速站点车流量预测方法
2024-11-05
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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