Application of neural network and FLAC to the back analysis of tunnel displacement

This paper studies the application of neural network and FLAC^3D to the back-analysis of displacements of tunnel displacement, using the learning and testing samples based on orthogonal test design and FLAC 3D numerical simulation. The potential mapping between parameters and surrounding rock displacement was established using neural network. The modulus of elasticity and lateral pressure coefficient of surrounding rock were obtained by verifing the precision of inversion parameter. The results show that it can solve the problem by searching parameters of back-analysis, which can be derived to achieve the displacement back analysis in tunnel displacement. The inversion results can be feedback for the design of tunnel. The results of back -analysis are accord with the accuracy of engineering.