岩体力学参数反演的代理蜜獾优化方法.

Aiming at the problem of time-consuming calculation due to a large number of numerical calculation models used in the back analysis of geomechanical parameters in complex underground engineering, a new bionic optimization surrogate back analysis method honey badger algorithm-Gaussian process regression-FLAC3D(HBA-GPR-FLAC3D) was proposed. The error between the numerical calculation results of the surrounding rock and the measured value was taken as the optimization objective function, and the geo-mechanical parameters was taken as the optimization variables. The HBA with excellent optimization performance was used to search for the global minimum value of the objective function. In the local optimization of the current optimal operator neighborhood, the GPR surrogate model was used as the operator fitness evaluation tool instead of the objective function constructed based on FLAC3D calculation. The research shows that compared with the back analysis method based on the bionic optimization algorithm, the number of numerical model calls of the proposed method is significantly reduced under the condition of the same calculation accuracy. It is suitable for rock mechanics parameters of complex underground engineering whose single-time numerical calculation is relatively time-consuming. [ABSTRACT FROM AUTHOR]