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Parallel Inversion of 1D Magnetotelluric Data Using Particle Swarm Optimization Algorithm

机译:使用粒子群优化算法并行反演1D MagnetOctellic数据

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The inversion of magnetotelluric data is a multi-parameter,nonlinear,and multimodal optimization problem.Particle swarm optimization (PSO) algorithm,which was developed by enlightenment of the behavior of birds in looking for food,is the fine solver for this geophysical inversion problem.As the forward problem becomes complex,the inversion becomes much more slow.We proposed a parallel PSO inversion algorithm to speedup the inversion of 1D magnetotelluric data.The numerical results show that the parallel PSO algorithm can speedup the inversion effectively and ensure the solution accuracy.
机译:MagnetOcturic数据的反转是一种多参数,非线性和多式化优化问题。群群优化(PSO)算法是通过对寻找食物的行为的启示而开发的,是这种地球物理反演问题的精细解决者转发问题变得复杂,反演变得更加慢。我们提出了一个并行PSO反转算法来加速1D磁音数据的反转。数值结果表明,并行PSO算法可以有效地加速反转并确保解决方案准确性。

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