Electrical fuzzy C-means: A new heuristic fuzzy clustering algorithm. Issue 1 (31st December 2016) - Mehdizadeh, Esmaeil; Golabzaei, Amir
Abstract: Many heuristic and meta-heuristic algorithms have been successfully applied in the literature to solve the clustering problems. The algorithms have been created for partitioning and classifying a set of data because of two main purposes: at first, for the most compact clusters, second, for the maximum separation between clusters. In this paper, we propose a new heuristic fuzzy clustering algorithm based on electrical rules. The laws of attraction and repulsion of electric charges in an electric field are conducted the same as the target of clustering. The electrical fuzzy C-means (FCM) algorithm proposed in this article use the electrical rules in electric fields and Coulomb's law to obtain the better and the realest partitioning, having respect to the maximum separation of clusters and the maximum compactness within clusters. Computational results show that our proposed algorithm in comparison with FCM algorithm as a well-known fuzzy clustering algorithm have good performance.