Three-dimensional site characterisation: neural network approach

Site characterisation is an important task in geotechnical engineering practice. The ultimate goal in site characterisation is to be able to estimate in situ soil properties at any half-space point at a site based on limited tests. This estimate may be a point estimate or expressed in terms of some statistical parameters. Geostatistical and random field methods have been applied with limited success. This paper presents a new approach, based on artificial neural networks, for site characterisation. Emphasis is placed on the application of generalised regression neural networks for site characterisation. The results show that the neural network approach has the potential to be a practical tool for site characterisation.