Title :
Study on Inventory Early-Warning in Supply Chains Based on Rough Sets and BP Neural Network
Author :
Jiang Hua ; Ruan Junhu
Author_Institution :
Inf. Dept., Hebei Univ. of Eng., Handan
Abstract :
The paper combines rough sets and ANN to analyze inventory early-warning in supply chains. The introduction of Rough sets cuts down the input dimensions of ANN, and the ANN algorithm is improved by adding the momentum factor mc and applying adaptive learning rate. Lastly, according to the inventory data of a manufacturing enterprise in Handan City, the paper proves the validity of the proposed model.
Keywords :
backpropagation; inventory management; neural nets; production engineering computing; rough set theory; supply chains; BP neural network; Handan city; adaptive learning rate; inventory management; rough sets; supply chains; Artificial neural networks; Biological neural networks; Costs; Inventory control; Inventory management; Neural networks; Raw materials; Rough sets; Supply chains; Transportation; BP neural network; inventory early-warning; rough sets; supply chains;
Conference_Titel :
Risk Management & Engineering Management, 2008. ICRMEM '08. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3402-2
DOI :
10.1109/ICRMEM.2008.118
