Fuzzy C-means algorithm with gravitational search algorithm in spatial data mining

There has been unprecedented growth of spatial data encountered in different application domains and their analysis has become more important and practically relevant. Clustering is one of the important tasks in spatial data mining and its issues have been extensively studied. In this paper, we propose a new hybrid approach for data clustering. Initially the proposed approach exploits spatial fuzzy c-means for clustering the vertex into homogeneous regions. In order to improve the performance of fuzzy c-means to cope with segmentation problems, we employ gravitational search algorithm which is inspired by Newton's rule of gravity. Gravitational search algorithm is incorporated into fuzzy c-means to take advantage of its ability to find optimum cluster centers which minimizes the fitness function of fuzzy c-means.