IDEAS home Printed from https://ideas.repec.org/a/ags/asagre/341795.html
   My bibliography  Save this article

Prediction of Total Output Value of Construction Industry in Jiangxi Province Based on Grey Prediction Model

Author

Listed:
  • Xu, Le
  • Liu, Yuangui

Abstract

In order to realize the accurate prediction of the total output value of construction industry in the future, the grey prediction model is used to compare the measured value with the predicted value from 2012 to 2021, and based on the existing data, the total output value of construction industry in Jiangxi Province in the next five years is predicted. The results show that the grey prediction model has a good prediction effect, and the error between the predicted value and the measured value is within 14%, which provides a basis for policy adjustment and resource optimization.

Suggested Citation

  • Xu, Le & Liu, Yuangui, 2023. "Prediction of Total Output Value of Construction Industry in Jiangxi Province Based on Grey Prediction Model," Asian Agricultural Research, USA-China Science and Culture Media Corporation, vol. 15(05), May.
  • Handle: RePEc:ags:asagre:341795
    DOI: 10.22004/ag.econ.341795
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/341795/files/3.PDF
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.341795?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

    Keywords

    Agribusiness;

    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:ags:asagre:341795. 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: AgEcon Search (email available below). General contact details of provider: .

    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.