关联规则中基于模糊遗传算法的研究与改进挖掘技术  

Research and improvement of association rule mining technology based on fuzzy genetic algorithm

作　　者：张军[1] 刘文杰[2] ZHANG Jun;LIU Wenjie(Jiangsu Maritime Institute,Nanjing 211170,China;School of Computer and Software,Nanjing University of Information Science & Technology,Nanjing 210044,China)

机构地区：[1]江苏海事职业技术学院,江苏南京211170 [2]南京信息工程大学计算机与软件学院,江苏南京210044

出　　处：《现代电子技术》2017年第14期23-25,29,共4页Modern Electronics Technique

基　　金：国家自然科学基金青年项目(61501247)

摘　　要：网络数据通常以爆炸式的聚集形式出现,导致曾提出的关联规则挖掘方法挖掘性能不好。基于上述原因,提出一种关联规则中基于模糊遗传算法的挖掘方法,此方法通过构建挖掘模型,将关联规则与模糊遗传算法融合在一起,进而给出待挖掘数据的适应度函数,并使用阈值对其进行限制。模糊遗传算法将对适应度函数进行交叉分配和编译分配,以改进方法的隶属度线性状态,获取更为有效的挖掘结果。实验结果表明,改进后的方法挖掘稳定性较强,挖掘精度较高,且挖掘时间较少。Network data usually appears in the form of explosive gather,which may lead to a bad performance of the association rule mining method proposed in the past.Based on the above reasons,a kind of association rule mining method based onfuzzy genetic algorithm(GA)is put forward in this paper,in which the mining model is built to fuse association rules and fuzzygenetic algorithm,and then give to the fitness function of the waiting mining data,and use threshold to limit it.Fuzzy genetic algorithm is used for cross distribution and compiling allocation of the fitness function to improve the method′s membership degreelinear state,and get more efficient mining results.The experimental results show that the improved method has strong mining stability,high mining precision and less mining time.

关 键 词：关联规则 模糊遗传算法 挖掘技术 挖掘精度 

分 类 号：TN911-34[电子电信—通信与信息系统] TP311.13[电子电信—信息与通信工程]