Novel dynamic clustering algorithm based on artificial immune network

作者：Zhong Jiang^*; Wu Zhong Fu; Wu Kai Gui; Ou Ling

来源：Acta Electronica Sinica, 2004, 32(8): 1268-1272.

• Clustering feasible solution
• Convergent probability
• Convergent speed
• Data sets
• Dynamic clustering
• Immune networks

Cluster analysis aims at answering two main questions: how many clusters there are in the data set and where they are located. Usually, the traditional clustering algorithms only focus on the last problem. In order to solve the two problems at the same time, this paper proposes a novel dynamic clustering algorithm called DCBIG, which is based on the immune network and genetic algorithm. The algorithm includes two phases, begins by running immune network algorithm to find a feasible solution, and then employs genetic algorithm to search the optimum number of clusters and the location of each cluster according to the feasible solution. Also, the probabilities and the conditions to acquire a feasible solution through immune network algorithm are discussed. Experimental results show that new algorithm is characterized by higher convergent probability and convergent speed.

• 出版日期2004
• 单位重庆大学