Research Article
Sales Forecasting of Traditional Fuel Passenger Vehicles in China Based on BP Neural Network-SARIMA Combination Model
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342671, author={Minjing Peng and Jianjin Liao}, title={Sales Forecasting of Traditional Fuel Passenger Vehicles in China Based on BP Neural Network-SARIMA Combination Model}, proceedings={Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17--19, 2023, Beijing, China}, publisher={EAI}, proceedings_a={ICEMME}, year={2024}, month={2}, keywords={bp neural network sarima bp neural network-sarima combination model conventional fuel passenger vehicles sales forecasting}, doi={10.4108/eai.17-11-2023.2342671} }- Minjing Peng
Jianjin Liao
Year: 2024
Sales Forecasting of Traditional Fuel Passenger Vehicles in China Based on BP Neural Network-SARIMA Combination Model
ICEMME
EAI
DOI: 10.4108/eai.17-11-2023.2342671
Abstract
Although the share of traditional fuel passenger vehicles and new energy passenger vehicles in the sales market changes frequently. However, few studies have explored the future development trend of traditional fuel passenger vehicles in the sales market. In this study, a combined BP neural network-SARIMA model is constructed to further improve the forecasting accuracy of the BP neural network model, and is used to forecast the monthly sales of traditional fuel-fired passenger vehicles in China in 2023. The results show that the combination model has better forecasting performance. This paper further observes the overall trend of monthly sales forecasts, and analyzes the abnormal fluctuations of sales in some months.
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