Genetic based interval type-2 fuzzy C-means clustering

Abstract

This paper deals with a genetic-based interval type 2 fuzzy c-means clustering (GIT2FCM), which automatically find the optimal number of clusters. A heuristic method based on a genetic algorithm (GA) is adopted to automatically determine the number of cluster based on the validity index. The proposed algorithm contains two main steps: initialize randomly the population of the GA and use the GA to adjust the cluster centroids based on the validity index which is computed by interval type 2 fuzzy c-means clustering (IT2FCM). The experiments are done based on datasets with the statistics show that the algorithm generates good quality of clusters. © 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.