ESTIMATION OF LATERAL WALL MOVEMENTS IN BRACED EXCAVATIONS USING NEURAL NETWORKS

The growing interest in neural networks among geotechnical engineers i s due to its excellent performance in modelling nonlinear multivariate problems. This paper demonstrates that neural networks can synthesize data derived from finite element studies on braced excavations in cla ys and capture the nonlinear interactions between the variables in the system. The neural network was able to produce reasonably accurate wa ll displacement predictions after ''learning'' from examples derived f rom finite element analyses. This method has the advantage over other more conventional methods in that it can be readily retrained as addit ional data from finite element studies and actual field records are ac quired.