Rayleigh wave dispersion inversion based on grasshopper optimization algorithm
YU Dongkai1, SONG Xianhai1,2, ZHANG Xueqiang1, ZHAO Sutao1, and CAI Wei1
1. Institute of Geophysics & Geomatics, China University of Geosciences(Wuhan), Wuhan, Hubei 430074, China;
2. Hubei Subsurface Multi-scale Imaging Laboratory(SMIL), China University of Geosciences(Wuhan), Wuhan, Hubei 430074, China
Abstract:As a new algorithm,the grasshopper optimization algorithm(GOA) belongs to swarm intelligent algorithms.It is inspired by the unique foraging behavior of grasshoppers at different stages.The movement of any grasshopper will be impacted by all the other grasshopper,which ensure the accuracy of convergence.In this paper,GOA is applied to invert surface-wave phase velocities.Using synthetic and real Rayleigh wave data,we examine the effectiveness and applicability of the GOA scheme in deducing an S-wave velocity profile for near-surface applications.The objective function in the proposed algorithm is proved to be able to rapidly converge to the global optimization solution.Another advantage of the proposed algorithm is a wide probability distribution of model parameters,which means this algorithm can define the scope of true-value and find the global minimum even in an extensive search space to guarantee the reliability of inversion results.
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