研究目的
To propose a new genetic algorithm method linked with Tikhonov’s regularization method (GA-TRM) for studying the inverse problem of surface-wave dispersion, aiming to improve inversion accuracy, reduce errors, and lower inversion instability.
研究成果
The GA-TRM method not only overcomes the issue with convergence to local minima that arises in the classical GA but also produces substantial improvement of the accuracy and the stability of inversion results. Future work should address the determination of regularization coefficients α using Tikhonov’s regularization method.
研究不足
The experimentally observed dispersion curves introduced into the inversion model are numerically calculated, making errors and noise in the curve ignorable. This deficiency prevents the adequate determination of regularization coefficients α, which should be corrected in future studies.
1：Experimental Design and Method Selection:
The study employs a genetic algorithm (GA) linked with Tikhonov’s regularization method (GA-TRM) to investigate the inverse problem of Rayleigh-wave dispersion. The GA includes selection for reproduction, crossing, and mutation operators.
2：Sample Selection and Data Sources:
A simple layered model is specified for the inversion of surface-wave dispersion, focusing on parameters μ and h, which have a substantial effect on the dispersion.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
The GA-TRM method is applied to the inversion problem, with the objective function incorporating a regularization operator to overcome convergence to local minima.
5：Data Analysis Methods:
The inversion results are compared with those obtained using the classical GA algorithm to evaluate improvements in accuracy and stability.
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