A Dolphin Herding Inspired Fuzzy Data Clustering Model and Its Applications

In this world of overwhelming data, efficient techniques are required to maintain this gigantic bulk of data. One of the renowned methods to serve this purpose is data clustering and hence is the objective of this paper. An algorithm is proposed which imitates the concept of herding, i.e., how dolphins catch their prey. It is an intelligent technique as all the data points are considered for every possible solution, providing clustering and ideal centroids in a short time. This paper presents the working of the algorithm on real datasets and extracts the results. The results of the proposed algorithm are then compared with well-known fuzzy c-means in terms of clusters formed presenting number of data items in each cluster, simplicity and coverage. The later part of the paper presents the association analysis technique on the clusters formed by the proposed approach with final section showing the cross comparisons made with respect to before and after clustering of data and for inter- and intra-clusters.