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作为全局非线性优化的新方法之一的遗传算法,近年来已从生物工程流行到大地电磁测深资料解释中.然而,大地电磁反演问题具有不适定性,解的非唯一性.通过结合求解不适定问题的Tikhonov正则化方法,本文采用实数编码遗传算法求解大地电磁二维反演问题.此算法在构建目标函数时引入正则化的思想,利用遗传算法求解最优化问题.常规的基于局部线性化的最优化反演方法易使解陷入局部极小值,而且严重的依赖初始模型的选择.与传统线性化的迭代反演方法相比,实数编码遗传算法能够克服传统方法的不足且能获得更好的反演结果.通过对大地电磁测深理论模型进行计算,结果表明:该算法具有收敛速度快、解的精度高和避免出现早熟等优点,可用于大地电磁资料解释.
In recent years, genetic algorithms, as one of the new methods for global nonlinear optimization, have been widely used in bio-engineering data interpretation of electromagnetic soundings in the earth. However, the problem of magnetotelluric inversion in the earth has ill-posedness and non-uniqueness. Tikhonov regularization method of ill-posedness problem.In this paper, the real-coded genetic algorithm is used to solve the two-dimensional electromagnetic inversion problem of geomagnetic field.This algorithm introduces the regularization principle when constructing the objective function, and solves the optimization problem by using genetic algorithm.The conventional algorithm based on local linear The optimal inversion method easily causes the solution to fall into local minimum and relies heavily on the choice of the initial model.Compared with the traditional linearized iterative inversion method, the real-coded genetic algorithm can overcome the shortcomings of traditional methods and obtain The results show that the proposed algorithm has the advantages of fast convergence rate, high precision of solution and avoiding precocity, which can be used to explain the electromagnetic data of the earth.