Title :
An empirical study of risk warning in supply chain based on BP neural network
Author :
Zhang, Ming-hong ; Lu, Liang
Author_Institution :
Dept. of Public Finance, Xiamen Univ., Xiamen, China
Abstract :
From the perspective of risk indicator of supply chain, this paper makes an empirical study of risk warning system in Sanming Steel Group in Fujian province. It discusses several indicators that cause risks to supply chain in company and categorize them. Then risk model is tested with artificial neural network to testify its applicability and accuracy. It´s argued that this is a rewarding attempt to go from academic level towards practical use and explores ways of thinking for risk warning system designing.
Keywords :
backpropagation; neural nets; risk management; supply chain management; BP neural network; Sanming Steel Group; artificial neural network; risk indicator; risk warning; supply chain; Artificial neural networks; Indexes; Neurons; Risk management; Steel; Supply chains; Training; artificial neural network; balanced score card(BSC)); risk warning; supply chain;
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
DOI :
10.1109/ISRA.2012.6219197
