Earticle

초록

영어

Since the idea of the supply chain management is proposed, many enterprises have attached great importance to the supply chain management and pay a lot of manpower and resources to study. It is also the focus to study the inventory in the field of the supply chain. Quantity of the inventory is not only related to the profit of the enterprises, but also related to the survival of the entire supply chain. Predicting the inventory can improve the ability of enterprises to prevent risk, increase the profits and reduce the losses. In order to predict better on inventory, we propose an improved BP neural network algorithm. In the algorithm, we use the improved GSA algorithm to optimize the parameters of BP neural network algorithm and improve the BP neural network algorithm aiming at its deficiency. The experimental results show that this method has good prediction effect.

목차

Abstract
 1. Introduction
 2. BP Neural Network Algorithm
 3. GSA
 4. The Improved BP Neural Network Algorithm
 5. Experiment
 6. Conclusion
 References

키워드

저자

• Fu-bin Pan [ School of Economics and Management, Xiamen University of Technology, Xiamen, 361024, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605