Application of BP Neural Network in the Prediction of Consolidation Coefficient

被引：1
|
作者：
Zhu, Hong-Hu [1 ]
Fu, Jian-Ping [2 ]
Dai, Fei [1 ]
机构：
[1] Hong Kong Polytech Univ, Dept Civil & Struct Engn, Hong Kong, Hong Kong, Peoples R China
[2] Beijing Univ, Beijing, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTATIONAL TOOLS FOR ENGINEERING APPLICATIONS | 2009年
关键词：
INFLECTION POINT METHOD;
D O I：
10.1109/ACTEA.2009.5227942
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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.
引用
收藏
页码：443 / +
页数：2
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