A data clustering algorithm based on mussels wandering optimization

As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intelligence algorithm called mussels wandering optimization (MWO) to the data clustering field, and proposes a new clustering algorithm by combining K-means clustering method and MWO. Tests on six standard data sets are performed. The results demonstrate the validity and superiority of the proposed method over some representative clustering ones.