Title :
Prediction of Seepage Quantities of Earthfill Dam Foundation Based on Artificial Neural Network
Author :
Peng, Hui ; Tian, Bin
Author_Institution :
Key Lab. of Geol. Hazards on Three Gorges Reservoir Area, China Three Gorges Univ., Yichang, China
Abstract :
In artificial neural network(ANN)method, the information treatment of the network are finished through interaction of neurones of the network. There are a series of advantages in the methodology, such as high degree non-linear, self-adaptation, self-learning, etc. Therefore the ANN method is used widely in the fields of prediction of physical quantities. In most cases, seepage equations show strong non-linear characteristics. This paper presents and establishes an ANN model based on the training method of learning into groups. Combining the practice of Xixia Researvoir, application of the ANN model to prediction of seepage quantities of the dam foundation is studied. There are high degree accuracy in the prediction result through using the ANN method. The results demonstrate that this method is widely available for the fields of dam safety monitoring and operation.
Keywords :
neural nets; water supply; ANN; Xixia Researvoir; artificial neural network; earthfill dam foundation; information treatment; nonlinear degree; safety monitoring; seepage equations; seepage quantities prediction; self adaptation; self learning; Accuracy; Area measurement; Artificial neural networks; Educational technology; Geologic measurements; Monitoring; Neurons; Nonlinear equations; Predictive models; Safety; earthfill dam; learning into groups; neural networks; prediction; seepage;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.273