一种反演问题求解的免疫克隆粒子群优化算法

为了克服标准粒子群优化(PSO)算法易陷入局部最优以及进化后期收敛速度慢等缺陷,分析了标准PSO算法早熟收敛的原因,提出了基于混合变异机制的免疫克隆粒子群优化(ICPSO)算法并将其应用到波阻抗反演问题中.克隆选择算子能够在局部极值点接近全局最优点时有效增强最优粒子跳出局部解的能力;引入混沌映射Tent序列加速最优粒子的变异学习,在局部极值点与全局最优点距离较远时扩大遍历范围,避免陷入局部极值.通过理论模型试算表明,ICPSO算法在进行波阻抗反演时不仅收敛速度快,而且具有较高的反演精度和抗噪性能.

Immune Cloning Particle Swarm Optimization for Wave Impedance Inversion

In the standard particle swarm optimization(PSO),the premature convergence of particles and slow convergence in the late process decrease the searching ability of the algorithm.By introducing the hybrid mutation mechanism,an immunity cloning PSO (ICPSO)algorithm was proposed and applied to the wave impedance inversion problem.When the local extremum is close to the global extremum,the proposed cloning selection operator can accelerate the best particle away form the local extremum. On the other hand,when the local extremum is far away from the global extremum,Tent sequence is adopted to extend the search scope and further the best particle mutation.Simulation for wave impedance inversion indicates that IPSO has better efficiency and higher accuracy.