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Evaluation model of green supply chain cooperation credit based on BP neural network.

Authors :
Chen, Jie
Huang, Shoujun
Source :
Neural Computing & Applications. Feb2021, Vol. 33 Issue 3, p1007-1015. 9p.
Publication Year :
2021

Abstract

More and more enterprises hope to achieve cooperation and win–win. However, many companies often have problems such as insufficient partner credit, which seriously affects the quality of cooperation. In order to effectively evaluate the credit, this paper constructs a personal credit evaluation model. The model compares the weight adjustment method with BP neural network and other methods. Compared with the BP neural network weight adjustment algorithm, the improved algorithm has obvious advantages in accuracy and convergence speed. The simulation results show that the green supply chain cooperation credit evaluation model can better evaluate the environmental behavior of enterprises. The BP neural network can better solve the problem of slow convergence and premature convergence, and can search data more accurately. The algorithm has good robustness. The evaluation model has high optimization accuracy, which shows that BP neural network can better learn and evaluate the credit of green supply chain at different levels. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*SUPPLY chains
*CREDIT
*COOPERATION

Details

Language :
English
ISSN :
09410643
Volume :
33
Issue :
3
Database :
Academic Search Index
Journal :
Neural Computing & Applications
Publication Type :
Academic Journal
Accession number :
148629047
Full Text :
https://doi.org/10.1007/s00521-020-05420-6