The invention discloses a probability distribution-based city anomaly detection method and device. The method comprises the following steps of: dividing a city region according to city road network data to obtain city sub-regions; vehicle track data are obtained through preprocessing; according to the vehicle trajectory data, time period traffic inflow and time period traffic outflow of the urban sub-regions in historical 30 days are counted, and then an inflow probability distribution set and an outflow probability distribution set of the urban sub-regions are constructed by using an FPD method; detecting and marking anomalies in the incoming flow probability distribution set and the outgoing flow probability distribution set by using an LOF algorithm; obtaining a current detection database of the to-be-detected city sub-region by finding out the approximate region; according to the current detection database, using an LOF algorithm to determine whether there is an abnormal event in the to-be-detected city sub-region on the current day; according to the method, the similarity between the regions is considered, anomaly detection is performed on the urban traffic flow in a probability distribution form, and an abnormal traffic flow mode can be effectively identified.
本发明公开了一种基于概率分布的城市异常检测方法及装置,包括:根据城市路网数据划分城市区域得到城市子区域;通过预处理得到车辆轨迹数据;根据车辆轨迹数据,统计城市子区域历史30天的时段交通入流量和时段交通出流量,再使用FPD方法构建城市子区域的入流量概率分布集合和出流量概率分布集合;使用LOF算法检测并标记入流量概率分布集合和出流量概率分布集合中的异常;通过找出近似区域得到待检测城市子区域的当前检测数据库;根据当前检测数据库使用LOF算法判断所述待检测城市子区域当天是否存在异常事件;本发明考虑区域之间的相似性,以概率分布的形式对城市交通流进行异常检测,能够有效的识别异常交通流模式。
City anomaly detection method and device based on probability distribution
一种基于概率分布的城市异常检测方法及装置
2024-05-14
Patent
Electronic Resource
Chinese
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