Clustering with Immunity-Vaccination Based on Particle Swarm Optimization Algorithm

This paper proposes a clustering algorithm based on Particle Swarm Optimization Algorithm with Immunity-Vaccination (IV-PSO-KMEANS). It combines Particle Swarm Optimization (PSO) algorithm and K-means for clustering. Synchronously, Immunity-vaccination and immunity-selection mechanisms of immune system are introduced into the iterative procedure. mmunity-vaccination is used to direct the procedure of particle swarm and immunity-selection is applied to select from the results of vaccination. In result, the swarm is made to move towards a better direction. The experiments show that the IV-PSO-KMEANS algorithm overcomes the problem of K-means algorithm that the results are related to the initial clustering centers, and the results of clustering are steadier and better than algorithms based on PSO.