基于凝聚层次聚类算法的公交扒窃犯罪热点分析方法  

An Analysis Method for the Hot Spot of Bus Pickpocketing Crime Based on Agglomerative Hierarchical Clustering Algorithm

作　　者：冯佳乐 姚远 FENG Jiale;YAO Yuan(Shanghai Triman Software Technology Co. Ltd., Shanghai 200042, China;Chongqing Public Security Bureau Police Supervision Corps, Chongqing 401147, China)

机构地区：[1]上海众恒软件技术有限公司,上海200042 [2]重庆市公安局警务督察总队,重庆401147

出　　处：《微型电脑应用》2022年第6期194-197,共4页Microcomputer Applications

摘　　要：公共交通在日常出行中占据重要地位,在为市民提供方便的同时,却也成为了扒窃者的聚集地,特别是在我国城镇化进程发展比较快的发达地区,发生在公共交通上的扒窃行为对治安稳定造成了持续性的影响。由于这种扒窃行为多发生在人员复杂、流动性大、现场难以取证等特殊的环境中,给案件的侦破带来很大的不确定性,可见客观环境决定了案件的发生概率,因此提高市民的主观防护意识,可以有效的避免案件的发生。我们通过整理以往公交扒窃行为数据,侧重分析犯罪位置数据,基于凝聚层次聚类算法,进行扒窃犯罪的热点分析,加强热点区域的防范宣传,减少扒窃犯罪的发生,进而提高市民的安全感。Public transport plays an important role in the daily travel.It not only provides convenience for citizens,but also poses a threat to citizens’property.Especially,in developed areas with rapid urbanization in China,pickpocketing on public transport has a lasting impact on public security and stability.Because such pickpocketing mostly occurs in complex personnel,high mobility,it is difficult to obtain evidence and other special environments,which brings great uncertainty to the detection of cases.The objective environment often determines the occurrence probability of cases.Therefore,improving citizens’subjective protection consciousness can effectively avoid the occurrence of cases.Based on sorting out the past bus pickpocketing behavior data,we focus on the analysis of crime location data.Based on the cohesion hierarchical clustering algorithm,we analyze the hot spots of pickpocketing crime,strengthen the prevention and publicity of hot spots,reduce the occurrence of pickpocketing crime,and then improve the citizens’sense of security.

关 键 词：凝聚层次聚类 犯罪热点 公交扒窃 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]