Evaluation of Chinese Enterprise Safety Production Resilience Based on a Combined Gray Relevancy and BP Neural Network Model

Jingjing Pei and Wen Liu
Additional contact information
Jingjing Pei: School of Engineering & Technology, China University of Geosciences-Beijing, Beijing 100083, China
Wen Liu: School of Engineering & Technology, China University of Geosciences-Beijing, Beijing 100083, China

Sustainability, 2019, vol. 11, issue 16, 1-13

Abstract: Improving the resilience of enterprise safety production is one of the important ways to deal with the frequency of safety accidents. Based on the definition of enterprise safety production resilience, we fully consider the impacts of recovery resilience, self-organizing resilience, and learning resilience as the three dimensions of enterprise safety production resilience. We build a back propagation (BP) neural network model that analyzes the main factors of enterprise safety production resilience using the results of gray relational analysis as an input that can assess the resilience of enterprise safety production and provide a valuable reference for the improvement of an enterprise’s safety production level. The results show that the resilience of production safety obviously increased after the Chinese enterprises with low resilience (as predicted by the model) adopted the corresponding early warning methods. The gray relational degree analysis method can incorporate well the variables for the establishment of the BP neural network prediction model.

Keywords: safety production; resilience; influencing factors; gray relational degree; BP neural network model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/16/4321/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/16/4321/ (text/html)

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:gam:jsusta:v:11:y:2019:i:16:p:4321-:d:256369

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().