Prediction Model of Concrete Dam Deformation Based on Adaptive Unscented Kalman Filter and BP Neural Network

Liang Hui Li; Sheng Jun Peng; Zhen Xiang Jiang; Bo Wen Wei

doi:10.4028/www.scientific.net/AMM.513-517.4076

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Prediction Model of Concrete Dam Deformation Based...

Prediction Model of Concrete Dam Deformation Based on Adaptive Unscented Kalman Filter and BP Neural Network

Abstract:

By using unscented kalman filter (UKF) theory and introducing adaptive factor into BP neural network, a new prediction model of concrete dam deformation was proposed. Example shows that this model can improve the convergence speed of BP neural network, and the calculation precision of this model meets engineering requirements. Meanwhile, this model can be applied in the safety monitoring of other hydraulic engineering structure.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

4076-4079

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.4076

Citation:

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Online since:

February 2014

Authors:

Liang Hui Li*, Sheng Jun Peng, Zhen Xiang Jiang, Bo Wen Wei

Keywords:

BP Neural Network (BPNN), Concrete Dam, Model, UKF Filter

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* - Corresponding Author

References

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