Clustering of data using fuzzy C-means (FCM) algorithm with aid of gravitational search optimization
R. Venkat, Srinivasulu Pamidi · 2017
There is a plenty of unorganized data available in various information repositories and examining this data is very necessary for some future analysis. Clustering this kind of data plays a vital role in knowing about formerly unknown and possibly useful data and also the concerns should be widely examined. Here, we are proposing a high level methodology for clustering the data. First of all the proposed methodology utilizes contiguous Fuzzy c-means (FCM) clustering the vertex into consistent regions. For Optimization we are using Gravitational Search Algorithm (GSA) based on law of gravity to overcome integration problems when dealing with Fuzzy C-means (FCM) Clustering. When applying GSA, gives better results by identifying optimum number of clusters and curtails the fitness function.