基于数据挖掘算法的犯罪相同特征向量集仿真  

Simulation of Criminal Same Feature Vector Set Based on Data Mining Algorithms

作　　者：李凌君[1] Li Lingjun(Department of Information Technology,Shaanxi Police Vocational College,Xi’an 710021,China)

机构地区：[1]陕西警官职业学院信息技术系,西安710021

出　　处：《兵工自动化》2024年第12期70-73,共4页Ordnance Industry Automation

基　　金：陕西省教育厅专项科学研究项目(18JK0961);陕西省教育厅一般专项科学研究项目(20JK0066)。

摘　　要：为提高犯罪数据挖掘准确率,有效打击犯罪,提出基于相同犯罪特征的数据挖掘算法。以公安系统数据库为基础,通过数据预处理,获得具有相同犯罪特征的数据向量集进行信息聚类,通过模糊集得到近似关系,依据贝叶斯公式将模糊集变为确定目标函数,依据目标函数,进行数据集划分相差较小的群组,获得数据挖掘结果。实验结果表明:该算法在犯罪特征的数据挖掘上,准确度和可靠性得到极大提升。In order to improve the accuracy of crime data mining and effectively combat crime,a data mining algorithm based on the same crime characteristics is proposed.Based on the public security system database,through data preprocessing,a set of data vectors with the same criminal characteristics are obtained for information clustering.The approximate relationship is obtained through the fuzzy set,and the fuzzy set is transformed into a determined objective function according to the Bayesian formula.Based on the objective function,the data set is divided into groups with smaller differences to obtain data mining results.The experimental results show that the algorithm has greatly improved accuracy and reliability in data mining of criminal features.

关 键 词：相同犯罪特征 数据挖掘 算法可靠性 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]