基于粒子群的模糊C均值聚类算法不同模式的比较

While the particle is encoded by membership, standard particle swarm algorithm (PSO) is applied into fuzzy C-mesns clustering algorithm (FCM), and detailed comparison is given when the algorithm using different models between asynchronous mode and synchronous mode. Firstly, PSO and related algorithms are introduced, then making standard PSO apply to FCM to deal clustering problems while encoded by membership. Finally, asynchronous mode is proved to be more excellent than synchronous mode on a certain extent, except on consuming time by experiments, making a good foundation on the research that PSO in terms of fuzzy clustering.