Predicting Subsurface Soil Layering and Landslide Risk with Artificial Neural Networks: a case study from Iran

This paper is concerned principally with the application of ANN model in geotechnical engineering. In particular the application for subsurface soil layering and landslide analysis is discussed in more detail. Three ANN models are trained using the required geotechnical data obtained from the investigation of study area. The quality of the modeling is further improved by the application of some controlling techniques involved in ANN. Based on the obtained results and considering that the test data were not presented to the network in the training process, it can be stated that the trained neural networks are capable of predicting variations in the soil profile and assessing the landslide hazard with an acceptable level of confidence.