IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/1404295.html
   My bibliography  Save this article

Improving Dam Seepage Prediction Using Back-Propagation Neural Network and Genetic Algorithm

Author

Listed:
  • Xuan Zhang
  • Xudong Chen
  • Junjie Li

Abstract

Statistical model is a traditional safety diagnostic model for dam seepage. It can hardly display the nonlinear relationship between dam seepage and the load sets and has the disadvantage of poor extension prediction. In this paper, the theories of Back Propagation Neural Network (BPNN) combined with Genetic Algorithm (GA) are applied to the seepage prediction model. Taking a typical dam in China as an example, the prediction results of BPNN-GA model and statistical model are compared with the monitoring values. The results show that the improved dam seepage model enhances the ability of nonlinear mapping and generalization and makes the seepage prediction more accurate and reasonable in the near future. According to the established criterion, the safety state of the dam in flood season is evaluated.

Suggested Citation

  • Xuan Zhang & Xudong Chen & Junjie Li, 2020. "Improving Dam Seepage Prediction Using Back-Propagation Neural Network and Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-8, April.
    • Handle: RePEc:hin:jnlmpe:1404295
    DOI: 10.1155/2020/1404295
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2020/1404295.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2020/1404295.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2020/1404295?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Ishfaque & Qianwei Dai & Nuhman ul Haq & Khanzaib Jadoon & Syed Muzyan Shahzad & Hammad Tariq Janjuhah, 2022. "Use of Recurrent Neural Network with Long Short-Term Memory for Seepage Prediction at Tarbela Dam, KP, Pakistan," Energies, MDPI, vol. 15(9), pages 1-16, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:1404295. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.