Prediction of Settlement of Soft Clay Foundation in Highway Using Artifical Neural Networks

Abstract

In recent years artificial neural networks (ANNs) have been applied to many geotechnical engineering problems with some degree of success. With respect to the design of Highway embankment, accurate prediction of settlement of soft clay foundation in highway is necessary to ensure appropriate structural and serviceability performance. In this paper, an ANN model is developed for predicting settlement of soft clay foundation based on the observation data of settlement. Approximately 200 data sets, obtained from the Field Tests and the published literature, are used to develop the ANN model. In addition, the paper discusses the choice of input and internal network parameters which were examined to obtain the optimum model. Finally, the paper compares the predictions obtained by the ANN with those given by a number of traditional methods. It is demonstrated that the ANN model outperforms the traditional methods and provides accurate settlement predictions for soft clay foundation in highway.