DocumentCode
3364067
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
fYear
2008
fDate
4-6 Nov. 2008
Firstpage
13
Lastpage
19
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Risk Management & Engineering Management, 2008. ICRMEM '08. International Conference on
Conference_Location
Beijing
Print_ISBN
978-0-7695-3402-2
Type
conf
DOI
10.1109/ICRMEM.2008.118
Filename
4673193
Link To Document