The invention provides a traffic anomaly detection method, device and equipment, a medium and a program product, and is applied to the technical field of urban intelligent traffic detection. The traffic anomaly detection method comprises the following steps: processing traffic state information based on a graph neural network and a long-short term memory network in response to received traffic state information in a to-be-detected time period at multiple intersections of a target area to obtain a traffic state feature vector; performing reconstruction processing on the traffic state feature vector to obtain trend reconstruction information of the traffic state and periodic reconstruction information of the traffic state; performing sequence decomposition on the traffic state information to obtain trend information of the traffic state and period information of the traffic state; based on the objective function, obtaining a reconstruction loss value according to the trend reconstruction information of the traffic state, the period reconstruction information of the traffic state, the trend information of the traffic state and the period information of the traffic state; and determining that the traffic state of the target area is abnormal in response to the condition that the reconstruction loss value is greater than a predetermined threshold.
本发明提供了一种交通异常检测方法、装置、设备、介质和程序产品,应用于城市智能交通检测技术领域。该交通异常检测方法包括:响应于接收到针对目标区域的多个路口处的待检测时段内的交通状态信息,基于图神经网络和长短时记忆网络对交通状态信息进行处理,得到交通状态特征向量;对交通状态特征向量进行重构处理,得到交通状态的趋势重构信息和交通状态的周期重构信息;对交通状态信息进行序列分解,得到交通状态的趋势信息和交通状态的周期信息;基于目标函数,根据交通状态的趋势重构信息、交通状态的周期重构信息、交通状态的趋势信息和交通状态的周期信息,得到重构损失值;以及响应于重构损失值大于预定阈值,确定目标区域的交通状态异常。
Traffic anomaly detection method, device, equipment, medium and program product
交通异常检测方法、装置、设备、介质及程序产品
2024-03-26
Patent
Elektronische Ressource
Chinesisch
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