Abstract: Since the PSO search accuracy is not high and its easy falling into the disadvantage of local minimum as a whole, this article proposes an improved particle swarm optimization algorithm. On the one hand the updated velocity formula using the weighted value of individual extreme of particles in particle swarm replaces the individual extreme of particles in this algorithm. On the other hand this improvement effectively enhances the convergence speed and optimal global searching ability of the particle swarm optimization by adjusting the inertia weight of two non-linear decreasing function. Then, the researchers verify the global convergence and optimal searching ability of the improved algorithm by simulating the four reference functions. Finally, the improved algorithm is applied to the optimized location of a 4G network base station in a city of the Pearl River Delta region.The results and applications demonstrate that the improved particle swarm optimization possesses greater optimized convergence speed and global searching ability.

Key words: Particle Swarm Optimization(PSO); weighted value; inertia weight; convergence and searching optimal; 4G network base station