Some applications of artificial neural network in geotechnical engineering

A MATLAB based backpropagation neural network model has been developed. Two major geo-engineering applications namely, slope movement and horizontal ground movement around tunnels, are identified. Data obtained from case studies are used to train and test the developed model and the ground movement is predicted with the help of input variables that have direct physical significance. A four-layered BPNN with an input layer, two hidden layers, and an output layer have been found optimal for the prediction of ground movement in both cases. The neural network results demonstrated a promising result predicting fairly successfully the ground behavior in both cases. If input variables influencing output goals are clearly identified and if a decent number of quality data are available, back propagation of neural network can be successfully applied as mapping and prediction tools in geotechnical perspective.