Abstract:

In order to establish an appropriate methodology of bank collapse prediction in the Three Gorges reservoir area, the article applied the artificial neural network method to study the bank collapse prediction. The method has the function of disposing the nonlinear relation. Through training, learning and simulation, it obtained the BP neural network model with a 7-32-14 network structure, and the correct prediction rate of it was 97.2%. Then  the model was used to forecast the reservoir bank collapse of Fengdu county when the water level was 175 m. Compared the forecast results with the traditional empirical formula calculation and the actual monitor data. The comparative results showed that the bank collapse prediction based on artificial neural network were very similar to the monitor data, and the deviation was less than 5 m. The average deviation of the formula calculation results and the monitor data was 15.9 m. For part of the slope sections, the formula calculation results were 8-11 meters,which was less than the actual monitor data. It failed to predict the true scope of bank collapse. In short, the average deviation of the bank collapse prediction results using artificial neural networks is about 3.8%. It is reliable and has higher precision.

Key words: Three Gorges reservoir, bank collapse prediction, non-liner, neural networks