Application of Improved BP Neural Network Model in Uplift Pressure Monitoring

Yi Tao Mei; Dong Jian Zheng; Lei Xu

doi:10.4028/www.scientific.net/AMR.304.24

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 304Application of Improved BP Neural Network Model in...

Application of Improved BP Neural Network Model in Uplift Pressure Monitoring

Abstract:

The network structure, initial weights and initial thresholds were optimized to solve some problems, such as over-fitting and slow convergence rate in standard BP Neural Network. Combining the base seepage character of concrete dam, a uplift pressure monitoring model is established in this paper with measured data of a actual concrete dam . The advantage of the presented model is tested and validated by actual examples. It has positive significance in the actual application.

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Periodical:

Advanced Materials Research (Volume 304)

Pages:

24-30

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.304.24

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Online since:

July 2011

Authors:

Yi Tao Mei, Dong Jian Zheng, Lei Xu

Keywords:

BP Neural Network (BPNN), Initial Parameter, Network Structure, Optimization, Uplift Pressure Monitoring

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References

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