FUZZY CLUSTERING USING GRAVITATIONAL SEARCH ALGORITHM

Abstract

Clustering is a key activity in numerous data mining applications such as information retrieval, text mining, image segmentation, etc. This research work proposes a clustering approach, Fuzzy-GSA, based on gravitational search algorithm (GSA) with parameter adaptation using fuzzy inference system. The parameter α, used in the calculation of the gravitational constant G, plays a crucial role in guiding the search process in GSA. Lower values of α increase search exploration, whereas higher values increase search exploitation. In the proposed Fuzzy-GSA approach, fuzzy inference rules are used to control the value of parameter α in GSA. The performance of the Fuzzy-GSA algorithm is evaluated against four benchmark datasets. The results illustrate that the Fuzzy-GSA approach attains the highest quality clustering when compared with several other clustering algorithms.