Proceedings of the Korean Geotechical Society Conference (한국지반공학회:학술대회논문집)
- 2000.11a
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- Pages.673-680
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- 2000
Estimating a Consolidation Behavior of Clay Using Artificial Neural Network
인공신경망을 이용한 압밀거동 예측
- Park, Hyung-Gyu (Dept. of Civil Engineering, University of Seoul) ;
- Kang, Myung-Chan (Dept. of Civil Engineering, University of Seoul) ;
- Lee, Song (Dept. of Civil Engineering, University of Seoul)
- Published : 2000.11.01
Abstract
Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, a back-propagation neural network model for estimating a consolidation behavior of clay from soil parameter, site investigation data and the first settlement curve is proposed. The training and testing of the network were based on a database of 63 settlement curve from two different sites. Five different network models were used to study the ability of the neural network to predict the desired output to increasing degree of accuracy. The study showed that the neural network model predicted a consolidation behavior of clay reasonably well.