An efficient clustering method for mobile users based on hybrid PSO and ABC. (2015) - Xu, Chong-huan
With the rapid development of mobile commerce, more and more researchers focus on mobile users segmentation. In this paper, we present an efficient clustering method which involves three sub-algorithms: K-harmonic means, particle swarm optimisation (PSO) and artificial bee colony (ABC). In order to overcome the problem of convergence to the local optimum, we use a hybrid nature-inspired algorithm, namely hybrid PSO and ABC, to solve them. In the process of evolution, the population is divided into two sub-groups. One evolves by PSO algorithm, and the other evolves by ABC algorithm. By the comparison of two fitness values generated by these different algorithms, respectively, we can get a better value. Finally, we will obtain the optimal value by iterative calculation. Detailed simulation analysis demonstrates the efficiency and effectiveness of our approach.