社区治安高危人员异常轨迹识别与预警方法研究*

为解决社区治安高危人员异常轨迹难以实时感知、精确识别、及时预警的问题，对社区治安高危人员动态轨迹进行标定，并建立动态轨迹序列化模型，通过序列化模型构建动态行为链；根据静态身份属性与动态轨迹时空特征信息，建立异常轨迹分析模型。结果表明:动态轨迹标定可实现对GPS轨迹数据高效、准确标定；异常轨迹分析模型可实现异常轨迹识别与预警。研究结果适用于社区高危人群管控，可为社区治安防控提供技术支持。

Research on identification and early-warning method of abnormal trajectories for high-risk community security personnel

In order to solve the problem that the abnormal trajectories of high-risk community security personnel are difficult to perceive in real-time,identify accurately and conduct early-warning timely,the calibration and sequential modeling on the dynamic trajectories of high-risk community security personnel were conducted,and based on the static identity attribute information and the temporal and spatial characteristic information of dynamic trajectory of the high-risk community security personnel,an analysis model of abnormal trajectory was established.Finally,a case study was conducted based on the Geolife dynamic trajectory dataset.The results showed that the proposed dynamic trajectory calibration method could achieve the efficient and accurate trajectory calibration of GPS trajectory data.The sequential modeling method of dynamic trajectory could construct a dynamic behavior chain based on the calibration results of dynamic trajectory.The analysis model of abnormal trajectory could realize the identification and early-warning of the abnormal trajectories of personnel.The results can be applied in the fields such as the management and control of high-risk community security personnel,and are expected to provide technical support for the community security prevention and control work.