基于人工神经网络的大坝变形分析与预报——以西津大坝27#点的变形监测为例

Analysis & Prediction of Dam Deformation Based on ANN——An Example of Deformation at Monitoring Point 27 of Xijin Dam

以MATLAB语言为基础,应用BP神经网络、逐步回归分析进行西津大坝27#点的变形分析与预报研究。在此基础上,进一步提出了逐步回归BP神经网络组合的预报方法,并探讨了3种方法的预报结果。研究表明,BP神经网络用于大坝变形分析与预报是可行的,所提出的逐步回归BP神经网络组合法提高了变形影响因子选择的科学性,在预报效果上,优于前两种方法。

On the basis of MATLAB programming language, BP neural network and stepwise regression are applied to predict the deformation at monitoring point No. 27 of Xijin dam. Furthermore, the combination prediction method of BP network and stepwise regression is put forward and the prediction results of 3 methods are compared. The research shows that it is feasible to apply BP neural network to dam deformation analysis and prediction. In addition, the combination method improves the scientific quality to choice deformation factors. The combination method is prior to the method of stepwise regression in prediction result and it is worth to further study.