【摘要】 针对粒子群优化算法应用于地震波阻抗反演问题时易陷入局部极小值和计算量大的问题,提出一种自适应免疫克隆粒子群(AICPSO)算法。该算法引入免疫机制,根据个体浓度和适应值概率定义了个体置换算子,能够避免粒子群算法陷于局部极值。为避免由进化过程中大量相同抗体引起的算法退化现象,根据记忆库和抗体群不同的特性,采用自适应变异算子更新记忆库,而依据抗体浓度和亲和度更新下一代抗体群体。经数值模拟和实际波阻抗资料反演表明,该算法不依赖于初始模型,收敛速度快且结果可靠。免疫粒子群优化算法为解决地震波阻抗反演问题提供了一条可行途径。更多还原

【Abstract】 An adaptive immune clonal particle swarm optimization(AICPSO) algorithm was presented to overcome the shortcoming of converging to local optimum and of massive computation the PSO algorithm is apt to fall when applied in seismic wave impedance inversion.The local extremum problem of PSO could be avoided in this algorithm due to defining the individual substitution operator,which is determined by fitness of individual and density probability based on imported immune mechanism.To prevent the algorithm degradation caused by a large number of the same antibodies during evolution,the memory base was modified by adaptive mutation operator and the swarm of antibodies of next generation was modified according to antibody concentration and affinity degree based on different properties of them.The proposed AICPSO is numerically simulated as well as being applied into actual seismic wave impedance inversion,and the data results show that it is not influenced by initial model,converges fast and has reliable result.AICPSO provides an effective means for seismic wave impedance inversion.更多还原