Abstract
In order to solve the problem that the production volume and sales volume of electronic products cannot be matched in time, it is necessary to predict the order and sales volume, and then effectively control the production volume of manufacturers. This article first introduces the basic steps of implementing the BP neural network algorithm, and then uses MATLAB software to fit the original data based on the BP neural network algorithm to predict the sales volume of the latest generation of products sold by customers to customers in the next 20 weeks and the latest generation of products in different sales. The region’s order volume in the next 20 weeks, and according to the forecast results to provide enterprises with production decisions to achieve timely matching of production volume and sales volume.
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Acknowledgement
2019 Basic Scientific Research Operational Expenses Scientific Research Project of Hei-longjiang Provincial Department of Education, no. : 2019-KYYWF-0474.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Sun, L., Yu, G., Zhang, Z. (2020). Research on Sales Forecast of Electronic Products Based on BP Neural Network Algorithm. In: Jiang, X., Li, P. (eds) Green Energy and Networking. GreeNets 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 333. Springer, Cham. https://doi.org/10.1007/978-3-030-62483-5_34
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DOI: https://doi.org/10.1007/978-3-030-62483-5_34
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