关键词: 聚类分析, 粒子群优化, 群算法, 人工免疫

Abstract: The paper adopts the Particle Swarm Optimization（PSO） to solve the parameters clustering problem of complex processes. The basic mechanism of PSO is presented in the paper. The clustering simulation on temperatures and rotation speeds of the calcination process verifies the practicability of PSO in parameters clustering of similar complex processes. The clustering features and parameters setting of PSO are discussed in detail. Combined with artificial immune, some improved methods are brought forward to achieve better performances.

Key words: clustering analysis, Particle Swarm Optimization（PSO）, swarm algorithm, artificial immune