The Application of PSO to the Nonlinear Inverse Problem of Magnetotelluric Sounding Data

摘要：

Particle swarm optimization (PSO) algorithm is a global optimization strategy that simulates the social behavior observed in a flock (swarm) of birds searching for food. It can find high quality solutions and converges fast and needs few parameters when applied to optimization searching in multi-dimension space function as well as dynamic target searching. This paper attempts to apply the newer PSO algorithm to the magnetotelluric data inversion and interpretation. Numerical tests of PSO algorithm are carried out in MATLAB 6.5. Theoretical and observed Magnetotell- uric (MT) data are used to test the performance of PSO. The results show that PSO algorithm be weak or even not depended on the initial models and can obtain the global optimal solution.

关键词： Particle swarm optimization (PSO) Nonlinear Magnetotelluric (MT) Inversion

作者: Min Xiao Xueming Shi Jianke Fan Guoshi Yang Xuhui Zhang

作者单位: the Institute of Geophysics and Geomatics, China University of GeoscieKey Laboratory of Exploration the Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074 China

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）