IDEAS home Printed from https://ideas.repec.org/a/igg/jismd0/v15y2024i1p1-18.html
   My bibliography  Save this article

Research on the Training of Broadcasting and Hosting Talents in Colleges and Universities Based on SARIMA-BP Prediction Model

Author

Listed:
  • Yang Zhou

    (SiChuan Film and Television University, China)

Abstract

In order to improve the employment adaptability of students majoring in broadcasting and hosting in colleges and universities, a prediction model is constructed by combining intelligent Seasonal AutoRegressive Integrated Moving Average (SARIMA) and Back Propagation Neural network (BPNN) in this study. This paper first analyzes the crisis faced by broadcasting professionals, and on this basis, SARIMA-BPNN model to analyze the demand of broadcasting professionals, taking Root Mean Squared Error as the evaluation index. The RMSE index value is 5.012, which shows that the SARIMA-BPNN model has a good prediction effect. Finally, this study predicts the changing trend of social demand for broadcasting talents, and then puts forward suggestions for the training of broadcasting host talents in colleges and universities to help promote the development of the training of broadcasting host talents in colleges and universities.

Suggested Citation

  • Yang Zhou, 2024. "Research on the Training of Broadcasting and Hosting Talents in Colleges and Universities Based on SARIMA-BP Prediction Model," International Journal of Information System Modeling and Design (IJISMD), IGI Global, vol. 15(1), pages 1-18, January.
  • Handle: RePEc:igg:jismd0:v:15:y:2024:i:1:p:1-18
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISMD.364102
    Download Restriction: no
    ---><---

    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:igg:jismd0:v:15:y:2024:i:1:p:1-18. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.