基于免疫记忆克隆的关联规则挖掘  

Association Rule Mining Based on Immune Memory Clonal Algorithm

作　　者：汪宏海[1] 

机构地区：[1]赣南教育学院计算机系,赣州341000

出　　处：《科学技术与工程》2012年第35期9537-9539,9551,共4页Science Technology and Engineering

摘　　要：针对数据关联规则挖掘的不足,提出了一种基于免疫记忆克隆算法的关联规则挖掘方法。算法利用了免疫记忆特性,把挖掘的关联规则存入记忆库,加快了挖掘速度。在克隆扩增过程中,设计了一种基于矢量距的抗体浓度计算方法,保证克隆扩增过程中解的多样性。仿真实验结果表明,现算法具有较快的运行速度,提高了所得关联规则的准确性。For the shortcomings of data association rules mining, a new association rule mining method based on immune memory clonal algorithm is proposed. The algorithm takes advantage of the immunological memory char- acteristics and mining association rules are stored in the memory, which speed up the mining speed. In the process of clonal expansion, an antibody concentration calculation method based on the vector is designed to ensure the di- versity of solutions in the process of clonal expansion. The simulation results show that the algorithm has a faster running speed and improve the accuracy of the obtained association rules.

关 键 词：免疫记忆克隆 关联规则 数据挖掘 抗体浓度 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]