The invention discloses a travel time prediction method and equipment based on a knowledge graph, and the method comprises the steps: building a traffic knowledge graph, storing a data layer in the traffic knowledge graph through employing a Neo4j graph database, enabling the traffic knowledge graph to comprise entities, relationships and attributes, enabling the entities to comprise at least one of a road condition, a road section, an intersection and a road grade, and enabling the relationships to be stored in the Neo4j graph database; the relationship comprises the relationship among the entities, and the attributes comprise travel time and traffic events; and acquiring real-time traffic data, and inputting the real-time traffic data into the traffic knowledge graph for prediction to obtain predicted travel time. According to the method, temporary or periodic changes caused by traffic events are considered, and the information is incorporated into the knowledge graph, so that the travel time prediction accuracy is improved.
本发明公开了一种基于知识图谱的行程时间预测方法及设备,包括:构建交通知识图谱,交通知识图谱中的数据层采用Neo4j图数据库进行存储,交通知识图谱包括实体、关系和属性,其中,实体包括路况、路段、路口、道路等级中的至少一项,关系包括各实体之间的联系,属性包括行程时间和交通事件;获取实时交通数据,并将实时交通数据输入到交通知识图谱进行预测,得到预测行程时间。本发明考虑由交通事件引起的临时性或周期性变化,并将这些信息纳入到知识图谱,进而提高行程时间预测准确性。
Travel time prediction method and device based on knowledge graph
基于知识图谱的行程时间预测方法及设备
14.03.2025
Patent
Elektronische Ressource
Chinesisch
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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