PSO算法计算函数极值时，常常出现早熟现象，导致求解函数极值存在较大的偏差，然而遗传算法对于函数寻优采用选择、交叉和变异算子操作，直接以目标函数作为搜索信息，以一种概率的方式来进行，因此增强了粒子群优化算法的全局寻优能力，加快了算法的进化速度，提高了收敛精度。(When PSO algorithm calculates function extremum, it often appears premature phenomenon, which leads to large deviation in solving function extremum. However, genetic algorithm uses selection, crossover and mutation operators for function optimization, and directly takes the objective function as the search information in a probabilistic way. Therefore, it enhances the global optimization ability of particle swarm optimization algorithm and speeds up the progress of the algorithm The convergence accuracy is improved.)