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
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