利用邻域粗糙集分析犯罪数据

Lydia J. Gnanasigamani, H. Seetha
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摘要

开展犯罪分析,找出犯罪事件的规律和联系。已经开展的研究的几个不同纬度是预测犯罪率,犯罪的社会学影响,社会经济因素对犯罪的贡献,以及寻找犯罪频率异常高的地方。地理信息系统和空间信息已发展成为犯罪数据的固有组成部分,因为这些信息是由警务机构公开的。“犯罪地图”指的是在特定地点绘制犯罪地图。犯罪的地理或空间信息在犯罪分析中起着重要的作用。先前的研究已经证明了空间在确定热点和显示特定地理上的犯罪分布方面的重要性。这项工作旨在利用粗糙集方法确定地理区域中区域之间的相似性。这样,我们就可以为邻居制定类似的打击犯罪策略,减少犯罪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Crime Data Using Neighbourhood Rough Sets
Crime analysis has been carried out to find out patterns and associations in crime incidents. A few of the different latitudes that research has been carried out are the prediction of crime rate, sociological impacts of crime, the contribution of socio-economic factors to the crime and finding the places where the frequency of crime is unusually high. GIS and spatial information have evolved as an inherent part of the crime data as the information is made public by the policing agencies. ‘Crime mapping' refers to mapping a crime to a particular place. Geography or the spatial information of crime plays an important role in the analysis of crime. Previous research have documented the spatial importance in identifying the hotspots and showing crime distribution in a particular geography. This work intends to identify the similarity between regions in the geographical area using Rough Set methodology. By doing so, we can prepare similar crime-fighting strategies for the neighbours and alleviate the crime.
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