In this research, behaviour of clayey soils under triaxial loading is studied using Neural Network. The models have been prepared to predict the stress-strain behaviour of remolded clays under undrained condition. The advantage of the model developed is that simple parameters such as physical characteristics of soils like water content, fine content, Atterberg limits and so on, are used to model the stress-strain behaviour of clays under triaxial loading, without performing exact and time-consuming tests on samples.
Results from the network show that neural network is a good tool for prediction of stress-strain behaviour of clayey soils using simple physical characteristics of such soils
S. M. Haeri, , & N. Sadati and R. Mahin-Rousta, (2001). Modelling of Stress-Strain Behaviour of Clayey Soils Using Artificial Neural Network. Journal of Advanced Materials in Engineering (Esteghlal), 20(2), 107-124.
MLA
S. M. Haeri; N. Sadati and R. Mahin-Rousta. "Modelling of Stress-Strain Behaviour of Clayey Soils Using Artificial Neural Network", Journal of Advanced Materials in Engineering (Esteghlal), 20, 2, 2001, 107-124.
HARVARD
S. M. Haeri, , N. Sadati and R. Mahin-Rousta, (2001). 'Modelling of Stress-Strain Behaviour of Clayey Soils Using Artificial Neural Network', Journal of Advanced Materials in Engineering (Esteghlal), 20(2), pp. 107-124.
VANCOUVER
S. M. Haeri, , N. Sadati and R. Mahin-Rousta, Modelling of Stress-Strain Behaviour of Clayey Soils Using Artificial Neural Network. Journal of Advanced Materials in Engineering (Esteghlal), 2001; 20(2): 107-124.
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