Study of Dam Deformation Model Based on Neural Network

Abstract:

Dam deformation analysis is one of the main tasks in dam safety monitoring. Regression analysis model is often used in dam deformation analysis in early days. At present, the statistical model, which divides the dam deformation into three parts, hydraulic pressure component, thermal component and ageing component, according to the causes of deformation, has been widely adopted in dam deformation analysis. The BP neural network model and the merging model based on BP neural network algorithm of dam deformation analysis are mainly discussed in this paper, and finally, the four models mentioned above are calculated and analyzed according to a specific project instance. The precisions are respectively ±1.19mm, ±0.38mm, ±0.34mm, and ±0.28mm for single linear regression model, statistical model, BP neural network model and merging model. So it is shown that the merging model is better than the others according to the results.

• Periodical: Applied Mechanics and Materials (Volumes 170-173)
• Pages: 2137-2142
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.170-173.2137
• Online since: May 2012
• Authors: Wu Sheng Hu, Fan Zhang, Lei Song, Hao Wang
• Keywords: Dam Deformation, Merging Model, Neural Network (NN), Regression Analysis, Statistical Model

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