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Sales Forecasting of Auto Retail Parts Based on BP Neural Network Analysis Model

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DOI: 10.23977/jwsa.2022.040101 | Downloads: 2 | Views: 54

Author(s)

Hao Zhang 1, Zhehua Zhang 1, Jun Jiang 1, Shuting Huang 2, Xinyan Wang 1

Affiliation(s)

1 Tibet University, Lhasa 850000, Tibet, China
2 Hainan University, Haikou 570000, Hainan, China

Corresponding Author

Zhehua Zhang

ABSTRACT

The economic system reform, automobile manufacturing industry has reached the peak of production, accompanied by the ensuing demand and supply of auto retail parts, how to achieve the purpose of forecasting the precise demand for auto retail parts, is to solve the current small class level of most auto retail parts enterprises and even store auto retail parts level to provide basic demand forecasting, and for enterprises and even manufacturers inventory management has a more It also has a faster categorization management method for enterprises and even manufacturers' inventory management.

KEYWORDS

BP neural network, Sales forecasting, Spss

CITE THIS PAPER

Hao Zhang, Zhehua Zhang, Jun Jiang, Shuting Huang, Xinyan Wang, Sales Forecasting of Auto Retail Parts Based on BP Neural Network Analysis Model. Journal of Web Systems and Applications (2022) Vol. 4: 1-6. DOI: http://dx.doi.org/10.23977/jwsa.2022.040101.

REFERENCES

[1] Ma Huan. Research on auto sales prediction model based on Baidu index and BP neural network [D]. Wuhan University of Technology, 2018. 16-17
[2] Cheng Li. Comparison of GDP forecasting models in Hunan Province [D]. Xiangtan University, 2021. DOI:10.27426/d.cnki.gxtdu.2021.001444.
[3] Zhang Shuo, Liu Kun, Li Xichang. Accurate demand forecasting of new retail products [J]. China collective economy, 2021(19):55-56.
[4] Wei F. Y., Li Q. F., Yan Y. T., and Zhang J. X. Research on sales prediction of new retail target products based on genetic neural network[J]. China Business Journal, 2021(18):32-35.DOI:10.19699/j.cnki.issn2096-0298.2021.18.032.

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