基于优化k -均值算法的犯罪分析与预测

S. Krishnendu, P. Lakshmi, L. Nitha
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引用次数: 10

摘要

在印度,犯罪率每天都在上升。在目前的情况下,最近的技术影响,社会媒体的影响和现代手段帮助罪犯实现他们的犯罪。犯罪分析和预测都是对犯罪模式进行分类和检验的系统化方法。目前已有各种聚类算法用于犯罪分析和模式预测,但它们并不能反映所有的要求。其中,K均值算法为预测结果提供了较好的方法。建议的研究工作主要集中在预测犯罪率高的地区和犯罪倾向多或少的年龄组。我们提出了一种优化的K均值算法来降低时间复杂度,提高结果的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Crime Analysis and Prediction using Optimized K-Means Algorithm
In India, the crime rate is increasing each day. In the current situation, recent technological influence, effects of social media and modern approaches help the offenders to achieve their crimes. Both analysis and prediction of crime is a systematized method that classifies and examines the crime patterns. There exist various clustering algorithms for crime analysis and pattern prediction but they do not reveal all the requirements. Among these, K means algorithm provides a better way for predicting the results. The proposed research work mainly focused on predicting the region with higher crime rates and age groups with more or less criminal tendencies. We propose an optimized K means algorithm to lower the time complexity and improve efficiency in the result.
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