Improved fuzzy clustering method based on swarm optimization algorithm

While particle swarm optimization(PSO) based fuzzy clustering algorithm is encoded by membership,the algorithm is less effective and tenderness to noise when processing the data set that the number of samples is less than the dimensions,so a new constraint strategy for fuzzy clustering is introduced by improving the constraint strategy of fuzzy clustering.When the sum of membership between a sample and all clusters is not one,after considering the membership obtained by PSO,the strategy further distributes the memberships on the basis of the distance between the sample and cluster centers,then making them meet the constraints of fuzzy clustering.The new strategy improves the clustering effect of the PSO based fuzzy clustering algorithm that encoded in membership significantly,and is verified by typical data sets.