Results obtained from ANN models were compared with simulation and experimental results and found close to them. For this purpose, cone penetration numerical simulations and cyclic triaxial tests conducted on Ottawa sand-silt mixes at different fines content were used. Received: 18 October 2013/Accepted: 2 April 2014 © Springer-Verlag Berlin Heidelberg 2014Ībstract This study deals with development of two different artificial neural network (ANN) models: one for predicting cone penetration resistance and the other for predicting liquefaction resistance. The use of neural networks for CPT-based liquefaction screening
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