基于时空信息的假币犯罪热点区域探测系统
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摘要
目前已有的犯罪热点分析方式是通过计算犯罪率或使用空间聚类方法,这些方法没有有效的利用时间信息,无法准确反映犯罪分布特征,且很难灵活地从不同层级去判断热点,同时在地图中进行实时渲染。本文采用基于时空数据场的层次聚类算法分析假币收缴数据,挖掘犯罪热点,设计并实现了假币犯罪热点区域探测系统,通过时空数据场理论可以充分融合时空信息,而层次聚类算法可以实现分级聚类,从而满足警方不同层级查看热点区域的需求。
At present,the analysis of crime hotspots is by calculating crime rate or using spatial clustering method.These methods do not use time information effectively and cannot accurately reflect the characteristics of crime distribution,and it is difficult to flexibly determine hotspots from different levels while performing real-time rendering in maps.This paper adopts a hierarchical clustering algorithm based on spatio-temporal data field to analyze the data of counterfeit currency seizures,mine criminal hotspots,and design and implement a hot currency area detection system for counterfeit currency crimes.Spatio-temporal data field theory can fully integrate spatio-temporal information,and hierarchical clustering algorithm can achieve hierarchical clustering,so as to meet the needs of police at different levels to view hot spots.
At present,the analysis of crime hotspots is by calculating crime rate or using spatial clustering method.These methods do not use time information effectively and cannot accurately reflect the characteristics of crime distribution,and it is difficult to flexibly determine hotspots from different levels while performing real-time rendering in maps.This paper adopts a hierarchical clustering algorithm based on spatio-temporal data field to analyze the data of counterfeit currency seizures,mine criminal hotspots,and design and implement a hot currency area detection system for counterfeit currency crimes.Spatio-temporal data field theory can fully integrate spatio-temporal information,and hierarchical clustering algorithm can achieve hierarchical clustering,so as to meet the needs of police at different levels to view hot spots.
引文
[1]孙峰华,李世泰,黄丽萍.中外犯罪地理规律实证研究.人文地理,2006,21(5):14-18.
[2]孙峰华,魏晓.犯罪地理学研究的新进展.人文地理,2004,19(5):60-63.
[3]Johnson S D.Repeat burglary victimization:A tale of two theories.Journal of Experimental Criminology,2008,4(3):215-240.
[4]赵勇,刘民,柏书华,等.系列入室盗窃案件的犯罪距离研究.中国人民公安大学学报:社会科学版,2010(2):143-149.
[5]Grubesic T H,Mack E A.Spatial-temporal interaction of urban crime.Journal of Quantitative Criminology,2008,24(3):285-306.
[6]Bowers K J,Johnson S D.Domestic burglary repeats and space-time clusters.European Journal of Criminology,2005,2(1):67-92.
[7]孙吉贵,刘杰,赵连宇.聚类算法研究.软件学报,2008,19(1):48-61.
[8]邓敏,刘启亮,李光强,等.基于场论的空间聚类算法.遥感学报,2010,14(4):702-709.
[9]Levine N.CrimeStat III.Washington DC:the National Institute of Justice,2009.
[10]Kulldorff M.A spatial scan statistic[J].Communications in Statistics-Theory and Methods.1997,26(6):1481-1496.
[11]Felson M,Poulsen E.Simple indicators of crime by time of day[J].International Journal of Forecasting.2003,19(4):595-601.
[12]Ratcliffe J H.The hotspot matrix:A framework for the spatio-temporal targeting of crime reduction[J].Police Practice and Research.2004,5(1):5-23.
[13]Nakaya T,Yano K.Visualising crime clusters in a space-time cube:An exploratory data-analysis approach using space-time kernel density estimation and scan statistics[J].Transactions in GIS.2010,14(3):223-239.
[14]Li Deyi,Du Yi.Artificial intelligence with uncertainty[M].Beijing:National Defence Industry Press,2005.
[2]孙峰华,魏晓.犯罪地理学研究的新进展.人文地理,2004,19(5):60-63.
[3]Johnson S D.Repeat burglary victimization:A tale of two theories.Journal of Experimental Criminology,2008,4(3):215-240.
[4]赵勇,刘民,柏书华,等.系列入室盗窃案件的犯罪距离研究.中国人民公安大学学报:社会科学版,2010(2):143-149.
[5]Grubesic T H,Mack E A.Spatial-temporal interaction of urban crime.Journal of Quantitative Criminology,2008,24(3):285-306.
[6]Bowers K J,Johnson S D.Domestic burglary repeats and space-time clusters.European Journal of Criminology,2005,2(1):67-92.
[7]孙吉贵,刘杰,赵连宇.聚类算法研究.软件学报,2008,19(1):48-61.
[8]邓敏,刘启亮,李光强,等.基于场论的空间聚类算法.遥感学报,2010,14(4):702-709.
[9]Levine N.CrimeStat III.Washington DC:the National Institute of Justice,2009.
[10]Kulldorff M.A spatial scan statistic[J].Communications in Statistics-Theory and Methods.1997,26(6):1481-1496.
[11]Felson M,Poulsen E.Simple indicators of crime by time of day[J].International Journal of Forecasting.2003,19(4):595-601.
[12]Ratcliffe J H.The hotspot matrix:A framework for the spatio-temporal targeting of crime reduction[J].Police Practice and Research.2004,5(1):5-23.
[13]Nakaya T,Yano K.Visualising crime clusters in a space-time cube:An exploratory data-analysis approach using space-time kernel density estimation and scan statistics[J].Transactions in GIS.2010,14(3):223-239.
[14]Li Deyi,Du Yi.Artificial intelligence with uncertainty[M].Beijing:National Defence Industry Press,2005.