Use of artificial neural networks for predicting settlement of shallow foundations on cohesionless soils / Mohamed A. Shahin.

Abstract

This thesis presents research which focuses on the settlement prediction of shallow foundations on cohesionless soils using artificial neural techniques. Previously, many methods have been developed to predict the settlement of shallow foundations, however methods that have the required degree of accuracy and consistency have not yet been developed. In this research artificial neural networks (ANNs) are used in an attempt to obtain more accurate settlement prediction. ANNs are linked with Monte Carlo simulation to provide a stochastic solution for settlement prediction that takes into account the uncertainties associated with settlement analysis. A set of stochastic design charts that provide the designer with the level of risk associated with predicted settlements are developed and provided.