Artificial neural network for stress-strain behavior of sandy soils: Knowledge based verification
in this paper, artificial neural networks (ANNs) are applied to model the stress-strain behavior of in situ sandy soils containing nonplastic fines. A main drawback of these types of models is discussed, i.e. an ANN based model gives no information how the model inputs affect the output. A systematic approach is therefore presented to acquire and verify the stored knowledge of a general ANN based constitutive soil model. Sensitivities of the output to corresponding inputs are defined mathematically. A sensitivity analysis is then performed to extract the dominant rules of the proposed model, which compare favorably with experimental observations. (c) 2005 Elsevier Ltd. All rights reserved.
artificial neural network stress-strain sandy soils sensitivity analysis undrained behavior