一种反演问题求解的免疫克隆粒子群优化算法  

Immune Cloning Particle Swarm Optimization for Wave Impedance Inversion

作　　者：聂茹[1,2] 岳建华[2] 邓帅奇[2] 刘仰光[2] 

机构地区：[1]中国矿业大学计算机学院,徐州221116 [2]中国矿业大学资源与地球科学学院,徐州221116

出　　处：《计算机科学》2009年第12期199-202,209,共5页Computer Science

基　　金：国家自然科学基金(50674086)资助

摘　　要：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。In the standard particle swarm optimization （PSO）, the premature convergence of particles and slow conver-gence 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 from 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.

关 键 词：粒子群 免疫粒子群 免疫克隆 波阻抗反演 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]