为了在聚类数不确定的情况下实现聚类分析,通过借鉴生物免疫系统中的克隆选择原理并结合聚类有效性分析,提出一种免疫模糊动态聚类算法。本算法不但可以根据数据自动确定聚类类目及中心位置,而且克服了传统聚类算法容易陷入局部极小值,对初始值敏感的缺点。仿真实验结果表明了本算法的有效性。
In order to achieve cluster analysis under the unknown amount of clustering, inspired by the clone selection principle of the vertebrate immune system and combining the cluster validity analysis, this paper proposed an immune-based dynamic fuzzy clustering algorithm. It not only adaptively determined the amount and the center' s positions of clustering, but also avoided the local optima and the flaw about sensitive to the initialization. Experimental results indicate the validity of the proposed algorithm.