IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/2783725.html
   My bibliography  Save this article

Improvement of English Teaching Process Management Based on Intelligent Data Sampling

Author

Listed:
  • Jin Cheng
  • Wei Liu

Abstract

In order to improve the management effect of English teaching process, this paper combines intelligent data to use technology to improve the management of English teaching process, improve the effect of English teaching, and construct an intelligent English teaching process management system. Moreover, this paper considers the interpolation problem of time series data in the metric space defined by dynamic time warping, and proposes an oversampling method for unbalanced time series data. In addition, this paper chooses to classify the Gaussian process model that is sensitive to unbalanced time series data to test the effect of the model. The experimental research results show that the English teaching process management system based on intelligent data sampling proposed in this paper can play an important role in English teaching management and can effectively improve the efficiency of English teaching.

Suggested Citation

  • Jin Cheng & Wei Liu, 2022. "Improvement of English Teaching Process Management Based on Intelligent Data Sampling," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, May.
    • Handle: RePEc:hin:jnlmpe:2783725
    DOI: 10.1155/2022/2783725
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/2783725.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2022/2783725.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/2783725?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
    ---><---

    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:2783725. 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.