Machine Learning Solution for Police Functions

A. P, Senthil Kumar A M, C. Vignesh, K. S
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Abstract

In our society, crime has become one of the most prevalent problems. Preventing it is of paramount importance. In order to prevent it, crimes must be tracked and a public database must be maintained so that case histories can be retrieved when necessary in the future. This project is being proposed to reduce criminal activities by developing predictive models. From past experiments, many people have used deep learning methods to identify patterns of only one particular crime from past criminal activities that took place in different countries. In this research work, machine learning is being applied to predict the states which have high crime rates by analyzing the past crime data. Consequently, the police can focus on those areas where crimes are likely to occur. To predict this, machine learning algorithms like Decision trees and Random Forest algorithms were being used to classify and give accurate information.
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警察职能的机器学习解决方案
在我们的社会中,犯罪已成为最普遍的问题之一。预防它是至关重要的。为了防止犯罪,必须对犯罪进行跟踪,并建立一个公共数据库,以便将来必要时能够检索到案件历史。提出这个项目是为了通过开发预测模型来减少犯罪活动。从过去的实验中,许多人使用深度学习方法从过去发生在不同国家的犯罪活动中识别出一种特定犯罪的模式。在这项研究工作中,机器学习被应用于通过分析过去的犯罪数据来预测犯罪率高的州。因此,警察可以集中在那些可能发生犯罪的地区。为了预测这一点,机器学习算法,如决策树和随机森林算法被用来分类和提供准确的信息。
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