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International Journal of Frontiers in Engineering Technology, 2019, 1(1); doi: 10.25236/IJFET.2019.010107.

Machine Learning Algorithm Generated Sales Prediction for Inventory Optimization in Cross-border E-Commerce

Author(s)

Jiahua Li1,*, Tao Wang,Zhengshi Chen,Guoqiang Luo

Corresponding Author:
Jiahua Li
Affiliation(s)

College of Information Engineering,Guangzhou Vocational and Technical University of Science and Technology, Guangzhou 510550, China
*Corresponding author e-mail:[email protected]

Abstract

With the continuous expansion of cross-border e-commerce enterprises' cross-border business activities and the rising operating costs of overseas warehousing, the cross-border e-commerce enterprise resource management system (ERP) is responsible for the management, coordination and optimization of global supply chain warehousing. On the cross-border e-commerce ERP platform, the product sales forecast and inventory optimization strategy realized by machine learning algorithm can effectively summarize the key factors, use the sales record big data, so that the forecast value, the expectations fit the actual value of the basic trend. The results show that the machine learning algorithm has good prediction effect and improved the best inventory equilibrium efficiency.

Keywords

Cross-border E-commerce, Machine Learning Algorithm, Enterprise Resource Management System (ERP)

Cite This Paper

Jiahua Li, Tao Wang,Zhengshi Chen,Guoqiang Luo. Machine Learning Algorithm Generated Sales Prediction for Inventory Optimization in Cross-border E-Commerce. International Journal of Frontiers in Engineering Technology (2019), Vol. 1, Issue 1: 62-74. https://doi.org/10.25236/IJFET.2019.010107.

References

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[2] Yi zhi Pan. Overseas Warehouse Construction and cross-border e-commerce logistics new mode exploration.(J). Logistics technology and applications, 2015, (09) : 130-133.
[3] Fang Ji,  Xiaheng Zhang. Cross-border e-commerce logistics mode and its evolution direction.( J). Western Forum, 2015(04) : 102-108.