Abstract：To overcome the problems of the particle swarm optimization (PSO)，such as relapsing into local extremum in the beginning stage of evolution，slow convergence and low convergence precision in the late stage， we propose a particle swarm optimization algorithm with nonlinear function (nfPSO)．In the nfPSO，use a nonlinear function of evolution iteration to control the inertia weight and accelerate coefficient．The experiment results demonstrate that the proposed algorithm is better in the convergence velocity and precision．
2009, Vol. 1 
