Improved fuzzy C-Means clustering algorithm based on particle swarm optimization algorithm

Abstract

Traditional FCM clustering algorithm has some problems, including sensitivity to initial values, local optimum and wrong division. In this paper, we proposed an improved fuzzy C-means clustering algorithm based on particle swarm algorithm. Firstly, we use PSO to determine the initial clustering center. Then define a new distance to reassign the fuzzy points. The experimental results show that this new algorithm not only reduces the number of iterations and makes the objective function value smaller, it also corrects some points with wrong division and improves the accuracy of classification results.