自适应多克隆聚类算法及收敛性分析  

An Adaptive Polyclonal Clustering Algorithm and Its Convergence Analysis

作　　者：马力[1,2] 焦李成[1] 白琳[2] 陈长国 

机构地区：[1]西安电子科技大学智能信息处理研究所,西安710071 [2]西安邮电学院信息中心,西安710061 [3]特维英数码科技西安有限公司,西安710075

出　　处：《模式识别与人工智能》2008年第1期72-81,共10页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.60372050);国家863计划项目(No.2002AA135080);陕西省自然科学基金项目(No.2002F26)资助

摘　　要：基于生物体免疫和克隆基本原理,提出一种自适应多克隆聚类算法.其核心思想是将多种人工免疫系统算子用于聚类过程,并以亲和度函数为依据自动调整聚类类别.算法引入重组算子来增加抗体种群中个体的多样性以扩大解的搜索范围,避免算法早熟现象.引入非一致变异算子增强局部求解的自适应性、优化局部求解性能,加快算法收敛速度.另外,还利用Markov链证明算法的收敛性.数据仿真实验结果表明该聚类算法能实现合理有效的聚类.Based on a simple description of the basic principle of biology immune and clonal process, a poly-clonal clustering algorithm with self-adaptive feature is put forward. The main idea of the algorithm is to put various operators in artificial immune system into clustering process and adjust clustering numbers automatically by affinity function. The recombination operator is introduced to increase the diversity of antibody group so as to broaden the search scope of the global optimization solution and avoid early mature phenomenon of the group. And the non-consistent mutation operator is introduced to enhance the adaptability and optimize the performance of local solution seeking, meanwhile convergence of the algorithm is speeded up. The experimental result shows that reasonable clustering could be realized by the proposed algorithm.

关 键 词：克隆选择 聚类分析 重组与交叉算子 非一致性变异 MARKOV链 收敛性 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]