WHO(Wild Horse Optimizer) is a novel intelligent optimization algorithm. The Rayleigh wave dispersion curve inversion is a complex iterative optimization problem with multi-parameter and multi-pole. WHO was introduced into the Rayleigh wave dispersion curve inversion in this study, where a modification was presented to improve the local search ability of the algorithm, and the inversion success rate was also proposed to evaluate the performance of the algorithm in the inversion of Rayleigh wave dispersion curve. Among the calculation of three-layer theoretical models, the inversion success rates of WHO were just 52%, 43% and 37%. However, the inversion success rates of MWHO (Modified Wild Horse Optimizer) were increased to 62%, 80% and 63%. In the calculation of four-layer theoretical models, the inversion success rates of PSO(Particle swarm optimizer) were 53%, 63% and 59%, MWHO were raised to 60%, 75% and 63%. In contrast to the calculation of theoretical model with noise, the success rate of MWHO was higher than that of WHO and PSO: the success rate of MWHO was 67%, the success rate of PSO was 53%, and the success rate of WHO was 42%. On this basis, WHO, PSO and MWHO were used to calculate the measured Rayleigh wave data. The success rate of MWHO was still higher than that of WHO and PSO: the success rate of MWHO was 55%, the success rate of PSO was 46%, and the success rate of WHO was 41%. The trial calculation statement of theoretical models and measured data: MWHO has advantages in inversion success rate, calculation accuracy and other aspects, and also has certain practical and research value.