中文摘要：

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．算法引入重组算予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．

英文摘要：

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.