Clustering Trend Predictions Using Evolutionary K-means Algorithm for Automated Clustering

The paper proposed a method of hybridization of k-means algorithm and evolutionary programming. The blend of the two generates k number of clusters C = (c1, ..., ck) in the data space D = {x1, ..., xn}. These clusters will evolve in such a way that prediction of the upcoming trends of clusters in the application is possible. The proposed hybrid is named as evolutionary k-means clustering algorithm which is useful in generating and predicting clustering trends in an automated system.