The invention relates to an urban traffic flow prediction method based on cluster federal learning, and belongs to the technical field of intelligent traffic. According to the method, a cluster-type federated learning framework is adopted, a space-time dependency relationship is mined on the basis of protecting privacy data, and a cluster-type traffic flow space-time prediction model is constructed; comprising the steps of acquiring urban traffic flow data information, constructing a cluster topological structure, predicting and calculating by a local client, aggregating cluster leader parameters, updating global parameters of a central server and the like. According to the method, the complex dependency relationship of the traffic data in time and space is considered in combination with the actual urban road network structure and the situation that data leakage is likely to happen to multiple participants, the data privacy is protected, and the prediction accuracy is improved.
本发明涉及一种基于集群式联邦学习的城市交通流量预测方法,属于智能交通技术领域。本方法采用集群式联邦学习框架,在保护隐私数据的基础上挖掘时空依赖关系,构建集群式交通流量时空预测模型,包括获取城市交通流量数据信息、构建集群拓扑结构、本地客户端预测计算、集群领导者参数聚合、中央服务器全局参数更新等。本发明在结合城市实际路网结构及多参与方易出现数据泄露的情况下,考虑了流量数据时间和空间上复杂的依赖关系,实现了保护数据隐私,提高了预测准确性。
Cluster type federated learning-based urban traffic flow prediction method
一种基于集群式联邦学习的城市交通流量预测方法
2024-12-03
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / 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 |
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