Expectation Maximization (EM) is a widely employed mixture model-based data clustering algorithm and produces … clustering algorithms. This paper presents an algorithm for the novel hybridization of EM and K-Means techniques for achieving … better clustering performance (NovHbEMKM). This algorithm first performs K-Means and then using these results it performs EM …

authors propose a Mobility Aware Clustering Scheme (MACS), which organizes the IoT devices in clusters using a fitness …

one, this technique was designed to solve combinatorial optimization problems, and by embedding a clustering algorithm …

Clustering is the process of analyzing data to find clusters of data objects that are similar in some sense to one … another. Some research studies have also extended the usage of clustering concept in inventory management. Yet, not many … research studies have considered the application of clustering approach on determining both optimal order quantity and loss …