Modelling the soil behaviour in uniaxial strain conditions by neural networks

The feed-forward neural network was used to simulate the behaviour of soil samples in uniaxial strain conditions, i.e. to predict the oedometer test results only on the basis of the basic soil properties. Artificial neural network was trained using the database of 217 samples of different cohesive soils from various locations in Slovenia. Good agreement between neural network predictions and laboratory test results was observed for the test samples. This study confirms the link between basic soil properties and stress-strain soil behaviour and demonstrates that artificial neural network can be successfully used as an effective alternative empirical material model.