Hybridization of Fuzzy C-Means and Fuzzy Social Spider Optimization for Clustering

摘要

Fuzzy clustering is most interested research problem in numerous real-world applications. The fuzzy c-means (FCM) is a most interested and widely used fuzzy clustering algorithm. However, it is easily stuck in the problem of local optima. Hence, the fuzzy social spider optimization (FSSO) technique has applied to solve fuzzy clustering problem in order to solve the shortcomings of FCM algorithm. Both FCM and FSSO have own advantages and disadvantages. In this presented research paper, the FCM clustering algorithm is an integrated with FSSO as a proposed method (FCM-FSSO) for solving fuzzy clustering problem in order to enhance clustering efficiency. The experimental outcome confirmed that the proposed hybrid FCM-FSSO clustering algorithms reveal improved performance compared with FCM and FSSO.