• HARISHBABU KALIDASU

Clustering methods works towards a set of multiple objects under clusters, so the objects in a particular cluster have a highest degree of similarity, however objects belongs to different clusters have a highest degree of dissimilarity. These type of methods are not only major tasks to expose basic structures of given set of data, but favourable tools expose the relations of input output complex system. FCM (Fuzzy C Means) is most used fuzzy cluster algorithms in real-time applications. Whereas the two major restrictions are there in FCM method. The first restriction is default number of clusters stated in-advance. The second one is to insert in minimal solutions. Here we proposed a new algorithm to enhance the clusters with FCM clustering. This algorithm tested with medical domain, results will shows the post processing refining or clarifying the clusters and enhance the quality of cluster. In this chapter presents a new algorithm to enhance the Fuzzy C Means. In this FCM algorithm, applied ant colony optimization algorithm to improve the quality of refining cluster.

cluster, ant colony optimisation, refining

"Improvement of Fuzzy C-Means Algorithm by using ACO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.504-513, April-2019, Available :http://www.jetir.org/papers/JETIR1904M76.pdf

"Improvement of Fuzzy C-Means Algorithm by using ACO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp504-513, April-2019, Available at : http://www.jetir.org/papers/JETIR1904M76.pdf