State of the Art of Artificial Neural Networks in Geotechnical Engineering

Abstract

Over the last few years, artificial neural networks (ANNs) have been used successfully for modeling almost all aspects of geotechnical engineering problems. Whilst ANNs provide a great deal of promise, they suffer from a number of shortcomings such as knowledge extraction, extrapolation and uncertainty. This paper presents a state-of-the-art examination of ANNs in geotechnical engineering and provides insights into the modeling issues of ANNs. The paper also discusses current research directions of ANNs that need further attention in the future.