DocumentCode :
3224015
Title :
Application of BP neural network in the prediction of consolidation coefficient
Author :
Zhu, Hong-Hu ; Fu, Jian-Ping ; Dai, Fei
Author_Institution :
Dept. of Civil & Struct. Eng., Hong Kong Polytech. Univ., Hong Kong, China
fYear :
2009
fDate :
15-17 July 2009
Firstpage :
443
Lastpage :
446
Abstract :
The application of artificial neural network (ANN) in the discipline of geotechnical engineering is discussed in this paper. A multi-layer error back-propagation (BP) feed-forward neural network model was proposed to predict an important geotechnical parameter, namely the consolidation coefficient. The conventional methods for predicting consolidation coefficient is briefly introduced. Based on the results of laboratory consolidation tests, the BP model was trained and used to determine the consolidation coefficient. The predicted values were compared to those determined by graphical methods. It is proved that the BP neural network approach yielded similar results compared with other methods.
Keywords :
backpropagation; feedforward neural nets; geophysics computing; geotechnical engineering; graph theory; BP neural network; artificial neural network; consolidation coefficient prediction; feed-forward neural network model; geotechnical engineering; graphical methods; multilayer error back-propagation neural network model; Artificial neural networks; Biological neural networks; Feedforward neural networks; Feedforward systems; Hydrogen; Laboratories; Multi-layer neural network; Neural networks; Predictive models; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computational Tools for Engineering Applications, 2009. ACTEA '09. International Conference on
Conference_Location :
Zouk Mosbeh
Print_ISBN :
978-1-4244-3833-4
Electronic_ISBN :
978-1-4244-3834-1
Type :
conf
DOI :
10.1109/ACTEA.2009.5227942
Filename :
5227942
Link To Document :
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