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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


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

Corresponding Author:
Jiahua Li

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


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.


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.


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