Crime Prediction Based on Statistical Models

Shubham Agarwal, Lavish Yadav, M. Thakur
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引用次数: 8

Abstract

Increasing rate of different crimes are always matter of concern in a peaceful society. Advancements in the field of information technology, publicly available information and services, somehow help criminals to achieve their misdeeds and involve them in much serious crimes than earlier. As a result, crime rate is increasing with a very high rate in developed and under-developed nations. Based on the previous year (s) crime details in Indian states, we present statistical models viz. Weighted Moving Average, Functional Coefficient Regression and Arithmetic-Geometric Progression based prediction of the crime in coming years. The crime details of Indian states between the years 2001 and 2013 have been used for this purpose. Crime details between 2001 and 2011 have been used for predicting the crimes for the years 2012 and 2013. These predicted values have been compared with actual crime details in the years 2012 and 2013. Difference between actual records and our predicted values for both years gives the accuracy of the proposed approaches between the range 85 % and 90%.
基于统计模型的犯罪预测
在一个和平的社会中,各种犯罪率的上升一直是人们关注的问题。信息技术领域的进步,公开可用的信息和服务,在某种程度上帮助罪犯实现他们的罪行,并使他们参与比以前更严重的犯罪。因此,在发达国家和欠发达国家,犯罪率都在以非常高的速度增长。根据印度各邦前一年的犯罪细节,我们提出了统计模型,即加权移动平均、功能系数回归和基于算术几何级数的未来几年犯罪预测。2001年至2013年间印度各邦的犯罪细节已被用于此目的。2001年至2011年的犯罪细节被用来预测2012年和2013年的犯罪。这些预测值与2012年和2013年的实际犯罪细节进行了比较。这两年的实际记录与我们的预测值之间的差异使得所提出的方法的准确度在85%到90%之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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