基于免疫算法的聚类分析与实现

在介绍自然免疫系统功能和特性的基础上，阐述了人工免疫算法的基本原理．从提取生物免疫系统的隐喻机制，基于免疫网络理论和克隆选择原理，建立了一种人工免疫数据聚类分析算法．并详细论述了该算法在电梯交通时段自动划分中的具体应用，MATLAB仿真表明该算法可以有效减少聚类数据的冗余信息，对解决交通时段自动划分等数据聚类问题是可行的和有效的．

The Clustering Analysis and Its Realization Based on Immune Algorithm

The paper introduces some important functions and character of nature immune system first and then states the basic principles of artificial immune algorithm. This work is mainly based on the immune network theory and the clone selection principle extracted from vertebrate immune systems. Experiments show that the given clus- tering algorithm can effectively reduce the redundant information of data, which especially fits the mass data clustering applications where hierarchical clustering algorithm or other traditional clustering algorithms may be ineffective.