大数据技术及遗传算法在数据挖掘中的应用研究  

Research on the Application of Big Data Technology and Genetic Algorithm in Data Mining

作　　者：越缙 YUE Jin(Anhui Wenda Univercity of Information Engineering,Hefei 231201,China)

机构地区：[1]安徽文达信息工程学院,安徽合肥231201

出　　处：《通化师范学院学报》2023年第8期80-87,共8页Journal of Tonghua Normal University

基　　金：安徽省人文社科重点项目“三维特效技术在游戏场景中的虚拟交互应用研究”(2022AH052847).

摘　　要：该文对关联规则挖掘、遗传算法和Hadoop平台等相关技术进行了介绍,在此基础上通过使用关联规则支持度来定义遗传算法的适应度函数,采用实数编码的方式对烘焙食品连锁店的交易数据属性值进行编码,形成染色体.为解决交叉概率和变异概率变化范围有限的问题,对两个概率公式进行自适应的优化.然后设计搭建了结合关联规则和遗传算法的连锁门店大数据挖掘平台.同时运用所设计的大数据平台收集数据对改进的遗传算法进行了实验验证,证实优化后的算法在处理复杂数据属性和收敛性上都具有一定优势.This paper introduces the related technologies such as association rule mining,genetic algo⁃rithm and Hadoop platform.On this basis,the fitness function of genetic algorithm is defined by using the support degree of association rules,and the attribute value of transaction data of bakery chain stores is en⁃coded in the way of real number coding to form chromosomes.Aiming at the problem that the variation range of crossover probability and mutation probability is limited,the two probability formulas are adap⁃tively optimized.Then,a chain store big data mining platform combining association rules and genetic algorithm is designed and built.At the same time,the improved genetic algorithm is tested by using the designed big data platform to collect data,which proves that the optimized algorithm has certain advan⁃tages in processing complex data attributes and convergence.

关 键 词：遗传算法 HADOOP 关联规则 适应度函数 遗传算子 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]