Inversion of the Rayleigh wave dispersion curves based on the sine-cosine algorithm

Rayleigh wave is widely used in engineering investigation and surveys.The inversion of its dispersion curves allows for effectively obtaining stratigraphic information.However,conventional global optimization algorithms in the dispersion curve inversion have a slow convergence rate and low convergence precision and are prone to prematurity.Therefore,this study introduced a novel global optimization algorithm—the sine cosine algorithm (SCA)—to solve the problems mentioned above.Based on the mathematical properties of sine and cosine functions,the SCA can adjust the exploration and development capabilities during the optimization using multiple random parameters and adaptive variables.As a result,it can ensure a high convergence rate and great stability while obtaining high-accuracy solutions.First,the feasibility of the SCA for the dispersion curve inversion was verified using four noise-free models.Then,the strong anti-interference ability of the SCA was proved by adding 15% of random noise to the models.Afterward,it was verified that SCA can yield high-precision,high-stability solutions in the dispersion curve inversion by comparison with the particle swarm optimization (PSO) approach.Finally,the practicability of the SCA was confirmed using seismic data from Arnarbælidi in Iceland and Wyoming in the USA.As indicated by the calculation results of theoretical models and the analysis of measured data,the SCA has a high processing speed,precision,stability,and practicability and thus allows for effective quantitative interpretation of the Rayleigh wave dispersion curves.