Model order selection for multiple cooperative swarms clustering using stability analysis

Extracting different clusters of a given data is an appealing topic in swarm intelligence applications. This paper introduces two main data clustering approaches based on particle swarm optimization, namely single swarm and multiple cooperative swarms clustering. A stability analysis is next introduced to determine the model order of the underlying data using multiple cooperative swarms clustering. The proposed approach is assessed using different data sets and its performance is compared with that of k-means, k-harmonic means, fuzzy c-means and single swarm clustering techniques. The obtained results indicate that the proposed approach fairly outperforms the other clustering approaches in terms of different cluster validity measures.