Study on Inventory Early-Warning in Supply Chains Based on Rough Sets and BP Neural Network

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.