A model on forecasting safety stock of ERP based on BP neural network

Author

Zhang, L. ; Wang, D. ; Chang, L.

Author_Institution

Sch. of Manage., Harbin Inst. of Technol., Harbin

fYear

2008

fDate

21-24 Sept. 2008

Firstpage

1418

Lastpage

1422

Abstract

Safety stock is one of the important parts of logistics management in ERP. This paper attempts to use artificial neural networks to forecast safety stock. Based on the index system of safety stock, this paper constructs a three-level BP neural network to analyze the principle and model of safety inventory. By using the samples to train and inspect the BP neural network, we conclude that the application of BP neural networks is an effective method to forecast safety stock, and can also be used to find the key factors for enterprises to improve their logistics management level.

Keywords

backpropagation; enterprise resource planning; logistics data processing; neural nets; stock control; BP neural network; ERP; artificial neural networks; enterprise management system; forecasting safety stock; logistics management level; safety inventory model; Artificial neural networks; Economic forecasting; Engineering management; Enterprise resource planning; Logistics; Materials requirements planning; Neural networks; Predictive models; Safety; Technology management; BP Neural Networks; ERP; Logistics Management; Safety Stock;

fLanguage

English

Publisher

ieee

Conference_Titel

Management of Innovation and Technology, 2008. ICMIT 2008. 4th IEEE International Conference on

Conference_Location

Bangkok

Print_ISBN

978-1-4244-2329-3

Electronic_ISBN

978-1-4244-2330-9

Type

conf

DOI

10.1109/ICMIT.2008.4654579

Filename

4654579