基于置信规则的犯罪区域识别专家系统
Belief Rule Based Expert System to Identify the Crime Zones
摘要：
本文主要研究犯罪区域识别问题。然后，它阐明了我们如何进行的信念规则库算法，以产生有趣的频繁模式的犯罪热点。本文还展示了我们如何使用专家系统来预测潜在的犯罪类型。为了进一步分析犯罪数据集，本文介绍了一个分析研究，结合我们的研究结果的吉大港犯罪数据集与人口统计信息，以捕捉可能影响邻里安全的因素。该解决方案的结果可用于提高对危险地点的认识，并帮助机构预测特定时间内特定地点的未来犯罪。
英文摘要：
This paper focuses on Crime zone Identification. Then, it clarifies how we conducted the Belief Rule Base algorithm to produce interesting frequent patterns for crime hotspots. The paper also shows how we used an expert system to forecast potential types of crime. In order to further analyze the crime datasets, the paper introduces an analysis study by combining our findings of the Chittagong crime dataset with demographic information to capture factors that could affect neighborhood safety. The results of this solution could be used to raise awareness of the dangerous locations and to help agencies predict future crimes at a specific location in a given time.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
