通信学报2017，Vol.38Issue(12)：21-33,13.DOI:10.11959/j.issn.1000-436x.2017287
基于改进密度聚类与模式信息挖掘的异常轨迹识别方法
Abnormal trajectory detection method based on enhanced density clustering and abnormal information mining
摘要
Abstract
Aiming at problems of low accuracy in the recognition and difficulty in enriching the information of abnormal behavior in the social security incidents,an abnormal trajectory detection method based on enhanced density clustering and abnormal information mining was proposed.Firstly,combined with Hausdorff distance,an enhanced DTW distance aiming at the problem of sampling to describe the behavior in detail was proposed.And based on the MBR distance,some definitions to describe the geographical distribution of trajectory were proposed.Secondly,with the densi-ty-distance decision model of CFSFDP algorithm,intelligent recognition of cluster was realized by using the difference of SSVR which was proposed based on SVR.Finally,based on the analysis of distribution under the two kinds of density,more abnormal information could be mined,three kinds of abnormal trajectories would be recognized.And the simula-tion results on trajectory data of Shanghai and Beijing verify that the algorithm is objective and efficient.Comparing to existing method,accuracy in the clustering is promoted by 10％,and the abnormal trajectories are sorted,abnormal in-formation is enriched.关键词
支持向量机回归/密度聚类/异常轨迹识别/模式信息挖掘Key words
SVR/density clustering/abnormal trajectory detection/pattern information mining分类
信息技术与安全科学引用本文复制引用
何明,仇功达,周波,柳强,曹玉婷..基于改进密度聚类与模式信息挖掘的异常轨迹识别方法[J].通信学报,2017,38(12):21-33,13.基金项目
江苏省自然科学基金资助项目(No.BK20150721,No.BK20161469) （No.BK20150721,No.BK20161469）
中国博士后基金资助项目(No.2015M582786,No.2016T91017) （No.2015M582786,No.2016T91017）
江苏省重点研发计划基金资助项目(No.BE2015728,No.BE2016904) （No.BE2015728,No.BE2016904）
江苏省科技基础设施建设计划基金资助项目(No.BM2014391) （No.BM2014391）
国家重点研发计划基金资助项目(No.2016YFC0800606)The Natural Science Foundation of Jiangsu Province (No.BK20150721,No.BK20161469),China Postdoctoral Science Foundation (No.2015M582786,No.2016T91017),The Primary Research & Development Plan of Jiangsu Province (No.BE2015728,No.BE2016904),The Engineering Research Center of Jiangsu Province (No.BM2014391),The National Key Re-search and Development Program of China (No.2016YFC0800606) （No.2016YFC0800606）
