An effective particle swarm optimization method for data clustering

Data clustering analysis is generally applied to image processing, customer relationship management and product family construction. This paper applied Particle Swarm Optimization (PSO) algorithm on data clustering problems. Two reflex schemes are implemented on PSO algorithm to improve the efficiency. The proposed methods were tested on seven datasets, and their performance is compared with those of PSO, K-means and two other clustering methods. Results show that our schemes are both robust and suitable for solving data clustering problems.