IDEAS home Printed from https://ideas.repec.org/a/ids/ijgeni/v46y2024i3-4p389-405.html
   My bibliography  Save this article

Food safety supply chain from perspective of big data algorithm and energy efficiency

Author

Listed:
  • Mian Deng
  • Yong Wang

Abstract

At present, food safety incidents emerge in an endless stream, so the relevant fields related to food safety issues have become a research hotspot. In order to effectively ensure food safety, it is necessary to control all aspects of the supply chain. In order to test the effect of Principal Component Analysis (PCA) and mutual Information Principal Component Analysis (MI-PCA) on the data set, the loss value and the predicted value of the data set were compared. The results show that the predicted value of PCA algorithm fluctuates obviously, while the predicted value of MI-PCA algorithm tends to be stable after 100 iterations. The prediction accuracy is also greater than 95%, and the prediction effect is good.

Suggested Citation

  • Mian Deng & Yong Wang, 2024. "Food safety supply chain from perspective of big data algorithm and energy efficiency," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 46(3/4), pages 389-405.
    • Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:389-405
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=137098
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijgeni:v:46:y:2024:i:3/4:p:389-405. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=13 .

    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.