In order to solve premature phenomenon and slow convergence problems in particle swarm algorithm, an improved mean particle swarm algorithm is provided. The algorithm apply to the nonlinear weight. At the same time in each iteration step, the history optimal particle and the global optimal population were averaged and multiplied a nonlinear weight so that it improve the global search capacity and convergence speed. Through four standard function test, The results show that the effectiveness of the proposed algorithm.