基于粒子群优化的模糊聚类分析  

PSO-based Fuzzy C-Mean Clustering Algorithm

作　　者：王玲[1] 贺兴时[1] 

机构地区：[1]西安工程大学理学院,西安710048

出　　处：《价值工程》2007年第11期96-98,共3页Value Engineering

基　　金：陕西省教育厅自然科学专项基金资助项目(项目编号:06JK286)

摘　　要：基于求解实优化问题时,粒子群优化算法优于遗传算法。在基于遗传算法的模糊C均值聚类算法基础上,给出了基于粒子群的模糊C均值聚类算法,试验结果表明:该算法克服了传统的模糊C均值聚类算法的缺陷,同时在收敛速度方面明显优于基于遗传算法的模糊C均值聚类算法。It is proved by experiments that the particle swarm optimization is superior to the genetic algorithm while solving the problems of real optimization.A kind of Fuzzy C-Mean Clustering based on Particle Swarm Optimization algorithm is provided on the basis of the genetic algorithm.The experimental results show that this algorithm avoids the limitation of FCM and is obviously superior to the FCM based on genetic algorithm.

关 键 词：模糊聚类 模糊C均值算法 遗传算法 粒子群优化算法 

分 类 号：O572.2[理学—粒子物理与原子核物理] O631.6[理学—物理]