Research Article
Research on Sales Forecast of Electronic Products Based on BP Neural Network Algorithm
@INPROCEEDINGS{10.1007/978-3-030-62483-5_34, author={Linan Sun and Guanghua Yu and Zhuo Zhang}, title={Research on Sales Forecast of Electronic Products Based on BP Neural Network Algorithm}, proceedings={Green Energy and Networking. 7th EAI International Conference, GreeNets 2020, Harbin, China, June 27-28, 2020, Proceedings}, proceedings_a={GREENETS}, year={2020}, month={11}, keywords={BP neural network Production volume Sales volume}, doi={10.1007/978-3-030-62483-5_34} }- Linan Sun
Guanghua Yu
Zhuo Zhang
Year: 2020
Research on Sales Forecast of Electronic Products Based on BP Neural Network Algorithm
GREENETS
Springer
DOI: 10.1007/978-3-030-62483-5_34
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.
