粒子群优化算法在函数均值求解中的应用研究

Application of particle swarm optimization on solving mean of function

针对函数的均值计算在工程与理论分析上的重要作用,在对粒子群优化算法(PSO)的整体极值、局部极值的模型进行调整的基础上,提出利用粒子群算法求解函数均值问题。该算法以当前所有粒子的平均值作为整体均值,粒子当前的平均值作为该粒子的局部均值,使粒子朝着目标函数的均值靠近,从而达到求出函数在一个区间段上的均值。数值计算结果验证了算法的有效性,并将其用于计算定积分,获得满意的结果。

Aimed at the significance of the mean of function in engineering and theoretical analysis,Particle Swarm Algo- rithm（PSO） is used to solving the mean of function by adjusting the model of goal extremum and local extremum of it.Using all particles＇present mean as goal mean and one particle＇s present mean as local mean,PSO can make particle move toward the mean of objective function,so it can find out the mean of function in a domain.The results of the numerical computation prove the method is effective,and it is used to compute definite integral.