EconPapers    
Economics at your fingertips  
 

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

Mian Deng and Yong Wang

International Journal of Global Energy Issues, 2024, vol. 46, issue 3/4, 389-405

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.

Keywords: supply chain; data dimensionality reduction; principal component; food safety; energy efficiency. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=137098 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:389-405

Access Statistics for this article

More articles in International Journal of Global Energy Issues from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijgeni:v:46:y:2024:i:3/4:p:389-405