基于改进粒子群算法的大地电磁反演  

Magnetotelluric Inversion Based on Improved Particle Swarm Optimization Algorithm

作　　者：李丽丽 李长伟[1,2] 程勃 陈汉波[1] 吕玉增 熊彬[1,2] 张媛[1] 黄杨 LI Li-li;LI Chang-wei;CHENG Bo;CHEN Han-bo;L Yu-zeng;XIONG Bin;ZHANG Yuan;HUANG Yang(College of Earth Sciences,Guilin University of Technology,Guilin 541000,China;Guangxi Key Laboratory of Concealed Metal Mineral Exploration,School of Earth Sciences,Guilin University of Technology,Guilin 541000,China)

机构地区：[1]桂林理工大学地球科学学院,桂林541000 [2]广西隐伏金属矿产勘查重点实验室,桂林541000

出　　处：《科学技术与工程》2023年第26期11098-11107,共10页Science Technology and Engineering

基　　金：国家自然科学基金(41464002);广西自然科学基金(2020GXNSFAA297079);桂林理工大学博士科研启动基金(GUTQDJJ2011038)。

摘　　要：粒子群算法是一种粒子群在全空间随机搜索的非线性反演方法,具有所需修改参数少、易于实现的优点,已在大地电磁(magnetotelluric,MT)反演得到了广泛应用,但其存在容易陷入局部最优解的缺点,在二维反演中应用较少且效果不好。提出了一种改进的优化粒子群算法,整个进化过程引入了局部进化,并且添加收缩因子和惯性权重参数,来改善该算法容易陷入局部最优解的缺点。最后将改进算法应用于二维MT反演,反演时在目标函数中加入添加先验信息的核函数,结果表明改进粒子群算法在过早收敛问题上有明显改善,反演异常体位置也与实际模型吻合较好。The particle swarm optimization(PSO)algorithm is a nonlinear inversion method of particle swarm random search in the whole space.It has the advantages of less modification parameters and easy implementation.It has been widely used in magnetotelluric(MT)inversion.However,it is easy to fall into the local optimal solution,which is less applied in two-dimensional inversion and the effect is not good.An improved optimized PSO was proposed.Local evolution was introduced in the whole evolution process.Shrinkage factor and incremental inertia weight factor were added to the velocity update formula,which improves the fault that the algorithm was easy to get into local extremal.Finally,the improved algorithm was applied to two-dimensional MT inversion.In the inversion,the kernel function sum with prior information was added to the objective function.The results show that the improved PSO algorithm has a obvious improvement in premature convergence,and the location of the inversion anomaly is also in good match with the actual model.

关 键 词：粒子群算法 全局进化 局部进化 核函数 MT反演 

分 类 号：P319[天文地球—固体地球物理学]