Inventory Forecasting for Medical Environmental Protection Equipment Enterprises Based on BP Neural Network Optimized by Sparrow Search Algorithm

DOI: https://doi.org/10.62517/jbdc.202301308

Author(s)

Zhenxu Liu1, Yanpu Huang2

Affiliation(s)

1School of Management, Shandong University of Technology, Zibo, Shandong, China 2Shandong Xinhua Medical Environment Protection Equipment Co., Ltd., Zibo, Shandong, China

Abstract

Deficiencies in corporate inventory forecasting are common problems, an inventory forecasting model using a sparrow search algorithm to de-optimize a BP neural network has been developed. Through the actual production of HX medical environmental protection equipment enterprises, the inventory of raw materials is studied, and the five factors that have the greatest impact on the inventory are selected. To establish an inventory forecasting model using the sparrow search algorithm to optimize the weights and thresholds of the BP neural network, and at the same time to compare and analyze the optimized model with the model before optimization. After comparing the results, it can be seen that the BP neural network optimized by the sparrow search algorithm is more stable and the prediction accuracy is more accurate than before, when predicting the inventory of the enterprise due to the optimization of the weights and thresholds.

Keywords

Sparrow Search Algorithm; Inventory Forecasts; BP Neural Network

References

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