Abstract: A novel fuzzy clustering algorithm which uses the merits of the global optimizing and higher convergent speed of Particle Swarm Opt imization(PSO) algorithm and combines with Fuzzy C-means(FCM) is proposed. The iteration process is replaced by the PSO based on the gradient descent of FCM, which makes the algorithm have a strong global searching capacity and avoids the local minimum problems of FCM. At the same time, FCM is no longer a large degree dependent on the initialization values. Numerical experiments show that the proposed algorithm is more accurate and efficient than FCM.

Key words: particle swarm optimization algorithm, fuzzy clustering, fuzzy C-means algorithm