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[1]沈兵,胡啸峰,吴建松.社区治安高危人员异常轨迹识别与预警方法研究*[J].中国安全生产科学技术,2021,17(4):171-177.[doi:10.11731/j.issn.1673-193x.2021.04.028]
　SHEN Bing,HU Xiaofeng,WU Jiansong.Research on identification and early-warning method of abnormal trajectories for high-risk community security personnel[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2021,17(4):171-177.[doi:10.11731/j.issn.1673-193x.2021.04.028]
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社区治安高危人员异常轨迹识别与预警方法研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
17
期数:
2021年4期
页码:
171-177
栏目:
职业安全卫生管理与技术
出版日期:
2021-04-30

文章信息/Info

Title:
Research on identification and early-warning method of abnormal trajectories for high-risk community security personnel
文章编号:
1673-193X(2021)-04-0171-07
作者:
沈兵; 胡啸峰; 吴建松
(1.中国人民公安大学 信息网络安全学院,北京 100076；
2.安全防范技术与风险评估公安部重点实验室，北京 100076；
3.中国人民公安大学 公共安全行为科学实验室，北京 100038;
4.中国矿业大学(北京) 应急管理与安全工程学院，北京 100083)
Author(s):
SHEN Bing;  HU Xiaofeng;  WU Jiansong
(1.School of Information and Network Security,People's Public Security University of China,Beijing 100076,China;
2.Key Laboratory of Security Prevention and Risk Assessment,Ministry of Public Security,Beijing 100076,China;
3.Public Security Behavioral Science Lab,People’s Public Security University of China,Beijing 100038,China;
4.School of Emergency Management and Safety Engineering,China University of Mining and Technology (Beijing),Beijing 100083,China)
关键词:
社区治安高危人员; 异常轨迹识别; 行为链; 轨迹标定; 序列化建模
Keywords:
high-risk community security personnel;  abnormal trajectory identification;  behavior chain;  trajectory calibration;  sequential modeling
分类号:
X956；X913.4
DOI:
10.11731/j.issn.1673-193x.2021.04.028
文献标志码:
A
摘要:
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。
Abstract:
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.

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备注/Memo

备注/Memo:
收稿日期： 2020-07-29
* 基金项目： 国家重点研发计划项目( 2018YFC0809700)；公安部科技强警基础工作专项项目( 2018GABJC01)
作者简介： 沈兵，硕士研究生，主要研究方向为机器学习与社会安全风险评估。
通信作者： 胡啸峰，博士，副教授，主要研究方向为风险评估与预测预警技术。
更新日期/Last Update: 2021-05-09