分析印度犯罪状况的轻量级方法研究

IF 1.1 Q3 CRIMINOLOGY & PENOLOGY
B. Saini, Dinesh Saini, S. Srivastava, Mayank Aggarwal
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引用次数: 2

摘要

摘要犯罪预测是为了降低犯罪率和减少社会犯罪活动。本文利用2001年至2019年的数据,重点监测印度的犯罪趋势。这项工作通过自上而下的方法分析了印度的犯罪状况,并实现了可视化和机器学习算法。印度热图可视化是为了关注所有邦的特定犯罪类型。此外,各种人口统计学,如年龄组、性别、种姓等,被认为对这个问题有更大的看法。该模型还提出了基于这些发现的积极措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study of Lightweight Approaches to Analyze Crime Conditions in India
Abstract Crime prediction is an effort to cut down the crime rate and criminal activities in the society. This paper concentrates on monitoring the crime trends in India using data from 2001 to 2019. The work analyzes the crime condition in India by following a top-to bottom approach and implementing visualization and machine learning algorithms. Heat map visualization of India is done to focus on specific crime types for all states. Furthermore, various demography of human population like age-groups, sex, caste, etc., are considered to have a larger perspective of the issue. The model also suggest proactive measures based on these findings.
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来源期刊
Journal of Applied Security Research
Journal of Applied Security Research CRIMINOLOGY & PENOLOGY-
CiteScore
2.90
自引率
15.40%
发文量
35
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