PARAMETER ESTIMATING APPROACH FOR CONDITIONED SOILS IN EPB SHIELD BY USING ARTIFICIAL NEURAL NETWORKS

摘要

Neural network models are developed for estimating model parameters of conditioned soils in EBP shield. The parameter identification of nonlinear constitutive model of soil mass is based on an inverse analysis procedure, which consists of minimizing the objective function representing the difference between the experimental data and the calculated data of the mechanical model. The weights of neural network are trained by using the Levenberg-Marquardt approximation which has a fast convergent ability. The parameter identification results illustrate that the proposed neural network has not only higher computing efficiency but also better identification accuracy. The results from the model are compared with simulated observations. The models are found to have good predictive ability and are expected to be very useful for estimating model parameters of conditioned soils in EBP shield.