Title :
A Novel Inventory Level Forecast Model Based on Artificial Neural Network
Author :
Li, Tong ; Zhang, Shuyun ; Xiong, Fengshan
Author_Institution :
Sch. of Bus., Agric. Univ. of Hebei, Baoding
Abstract :
Zero inventory is the ideal state in the inventory management, especially to the innovative products, it can not only reduce costs but also promote the development of the new products. In order to forecast the enterprise inventory scientifically and accurately, according to the principle of artificial neural network, this paper proposes the BP neural network model for the forecast of the enterprise inventory. The model not only can simulate the expert in forecasting the enterprise inventory, but also avoid the subjective mistakes in the forecasting process. The enterprise inventory forecast about the portable computer of Baoding City in 12 months shows that the results given by this model are reliable, and the method to forecast the enterprise inventory is feasible.
Keywords :
backpropagation; forecasting theory; inventory management; neural nets; BP neural network model; artificial neural network; cost reduction; enterprise inventory; forecasting process; innovative products; inventory level forecast model; inventory management; zero inventory; Artificial neural networks; Cities and towns; Costs; Information technology; Inventory management; Mathematical model; Neural networks; Neurons; Predictive models; Technology forecasting; BP neural network; artificial neural network; forecast model; inventory level;
Conference_Titel :
MultiMedia and Information Technology, 2008. MMIT '08. International Conference on
Conference_Location :
Three Gorges
Print_ISBN :
978-0-7695-3556-2
DOI :
10.1109/MMIT.2008.114