IDEAS home Printed from https://ideas.repec.org/a/bpj/jossai/v7y2019i5p486-496n7.html
   My bibliography  Save this article

An Extended Grey Model GM(1, 1, exp(bk)) and Its Application in Chinese Civil Air Passenger Volume Prediction

Author

Listed:
  • Cheng Maolin

    (School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou, 215009, China)

  • Shi Guojun

    (School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou, 215009, China)

  • Han Yun

    (School of Business, Suzhou University of Science and Technology, Suzhou, 215009, China)

Abstract

In grey models, GM(1, 1) is an important prediction model. The grey model GM(1, 1) has good prediction results in the case original data change exponentially at a low speed. However in practical cases sometimes, original data show exponential changes or approximately exponential changes change at a high speed. In these cases, the grey model GM(1, 1) has poor prediction results because the data fail to meet the laws of traditional model. Therefore, the paper proposes an extended grey model GM(1, 1, ebk) and its modeling method. In the final section, the paper builds grey models of GM(1, 1, ebk) for a practical problem and the results show the grey model proposed has greatly improved simulation and prediction accuracy compared with the traditional model.

Suggested Citation

  • Cheng Maolin & Shi Guojun & Han Yun, 2019. "An Extended Grey Model GM(1, 1, exp(bk)) and Its Application in Chinese Civil Air Passenger Volume Prediction," Journal of Systems Science and Information, De Gruyter, vol. 7(5), pages 486-496, October.
    • Handle: RePEc:bpj:jossai:v:7:y:2019:i:5:p:486-496:n:7
    DOI: 10.21078/JSSI-2019-486-11
    as

    Download full text from publisher

    File URL: https://doi.org/10.21078/JSSI-2019-486-11
    Download Restriction: no
    File URL: https://libkey.io/10.21078/JSSI-2019-486-11?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
    ---><---

    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:bpj:jossai:v:7:y:2019:i:5:p:486-496:n:7. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.