Numerical Simulation of Strength Limit of Surrounding Rock in Geotechnical Engineering Based on Machine Learning

When the traditional method numerically simulates the strength of the surrounding rock, the error of obtaining the strength parameters is large, which leads to a large range of the numerical value of the strength simulation. Therefore, a numerical simulation method based on machine learning for the strength limit of surrounding rock in geotechnical engineering is proposed. Evaluate the volume joints and structural surfaces of the surrounding rock, collect the surrounding rock environment information and geotechnical characteristics, perform mechanical simulation on it, use machine learning technology to optimize the strength parameter algorithm, obtain the optimal stress parameter, and realize the strength numerical simulation. The experimental results show that the variation range of numerical simulation method of surrounding rock strength is less than that of two traditional methods, which improves the accuracy of numerical simulation.