Manufacturing Big Data Modeling Algorithm Based on GM (1,1) - LSTM and Its Application in Sales Forecasting

It is a new period for the development of automobile industry, the economic situation is complex and changing, and the policies of automobile industry are frequently issued, so accurate prediction of automobile sales is extremely important and practical for both government and enterprises. In this p...

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Published in:Data Driven Control and Learning Systems Conference (Online) pp. 1171 - 1175
Main Authors: Long, Yinren, Xiao, Yi, Ren, Hongru, Lu, Renquan
Format: Conference Proceeding
Language:English
Published: IEEE 12.05.2023
Subjects:
Big Data
Big Data Modeling
Data models
Industries
Manufacturing Enterprise
Neural networks
Prediction algorithms
Predictive models
Resistance
Sales Forecasting
ISSN:2767-9861
Online Access:Get full text
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Abstract It is a new period for the development of automobile industry, the economic situation is complex and changing, and the policies of automobile industry are frequently issued, so accurate prediction of automobile sales is extremely important and practical for both government and enterprises. In this paper, the GM(1,1) model and the long short-term memory (LSTM) neural network model are combined and optimized, and the sales of a brand of cars from January 2019 to September 2022 are used as sample data, and the car sales in the next three months are predicted by two single models and linear combination forecasting models, respectively. The experimental results show that the linear combined forecasting model outperforms the other two single models in terms of forecasting results and has better resistance to the interference of external factors.
AbstractList It is a new period for the development of automobile industry, the economic situation is complex and changing, and the policies of automobile industry are frequently issued, so accurate prediction of automobile sales is extremely important and practical for both government and enterprises. In this paper, the GM(1,1) model and the long short-term memory (LSTM) neural network model are combined and optimized, and the sales of a brand of cars from January 2019 to September 2022 are used as sample data, and the car sales in the next three months are predicted by two single models and linear combination forecasting models, respectively. The experimental results show that the linear combined forecasting model outperforms the other two single models in terms of forecasting results and has better resistance to the interference of external factors.
Author Ren, Hongru
Lu, Renquan
Long, Yinren
Xiao, Yi
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Snippet It is a new period for the development of automobile industry, the economic situation is complex and changing, and the policies of automobile industry are...
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StartPage 1171
SubjectTerms Big Data
Big Data Modeling
Data models
Industries
Manufacturing Enterprise
Neural networks
Prediction algorithms
Predictive models
Resistance
Sales Forecasting
Title Manufacturing Big Data Modeling Algorithm Based on GM (1,1) - LSTM and Its Application in Sales Forecasting
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