Comparative Study of Fuzzy PSO (FPSO) Clustering Algorithm and Fuzzy C-Means (FCM) Clustering Algorithm

Abstract

Swarm intelligence that mimic the natural collective intelligence to solve the computational problem has emerged and widely used in data mining. Particle swarm optimization (PSO) is a kind of swarm intelligence algorithm. Fuzzy clustering is an important research in several real-world applications. Fuzzy particle swarm optimization (FPSO) is a fuzzy clustering algorithm that can be optimized with the use of PSO algorithm to get global optima. Fuzzy c-means (FCM) is one of the most popular fuzzy clustering techniques. In this paper, FPSO and FCM clustering algorithms will be implemented. These two methods were compared in term of execution times and fuzzy objective function ( �� ) by using datasets namely Iris Plants, Breast Cancer and Wine from UCI (University of California) Machine Learning repository.