Estimating the Maximum Shear Modulus with Neural Networks

2013 ◽  
pp. 684-693
Author(s):  
Manuel Cruz ◽  
Jorge M. Santos ◽  
Nuno Cruz
Keyword(s):  
Neural Networks ◽  
Shear Modulus

Application of Artificial Neural Networks for the prediction of undrained shear modulus in cohesive soils

ce/papers ◽  
2018 ◽  
Vol 2 (2-3) ◽  
pp. 833-838
Author(s):  
Grzegorz WRZESIŃSKI ◽  
Zbigniew LECHOWICZ ◽  
Maria J. SULEWSKA
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Shear Modulus ◽  
Cohesive Soils ◽  
Artificial Neural ◽  
Undrained Shear

Estimation of Dynamic Properties of Sand Using Artificial Neural Networks

1996 ◽  
Vol 1526 (1) ◽  
pp. 1-5
Author(s):  
S. H. Ni ◽  
C. H. Juang ◽  
P. C. Lu
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Shear Modulus ◽  
Dynamic Properties ◽  
Damping Ratio ◽  
Soil Parameters ◽  
Overburden Pressure ◽  
The Neural Network ◽  
Artificial Neural

Dynamic properties of soils are usually determined by time-consuming laboratory tests. This study presents a method for estimating dynamic soil parameters using artificial neural networks. A simple feedforward neural network with back-propagation training algorithm is used. The neural network is trained with actual laboratory data, which consists of six input variables. They are the standard penetration test value, the void ratio, the unit weight, the water content, the effective overburden pressure, and the mean effective confining pressure. The output layer consists of a single neuron, representing shear modulus or damping ratio. Results of the neural network training and testing show that predictions of shear modulus by the neural network approach is reliable although it is less successful in predicting damping ratio.

Modelling damping ratio and shear modulus of sand–mica mixtures using neural networks

2009 ◽  
Vol 104 (1-2) ◽  
pp. 31-40 ◽  
Author(s):  
Ali Firat Cabalar ◽  
Abdulkadir Cevik
Keyword(s):  
Neural Networks ◽  
Shear Modulus ◽  
Damping Ratio

Determination of S-N curves with the application of artificial neural networks

1999 ◽  
Vol 22 (8) ◽  
pp. 723-728 ◽  
Author(s):  
Artymiak ◽  
Bukowski ◽  
Feliks ◽  
Narberhaus ◽  
Zenner
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural

Review of Pattern Recognition by Self-Organizing Neural Networks.

1995 ◽  
Vol 40 (11) ◽  
pp. 1110-1110
Author(s):  
Stephen James Thomas
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Self Organizing
Sign in / Sign up

Export Citation Format

Share Document