Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China

Research Article

Forecast of Steel Price on ARIMA-LSTM Model

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  • @INPROCEEDINGS{10.4108/eai.18-11-2022.2326770,
        author={Haidi  Wu and Mingxun  Li and Kimhong  Lim and Cunrong  Li},
        title={Forecast of Steel Price on ARIMA-LSTM Model},
        proceedings={Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China},
        publisher={EAI},
        proceedings_a={ICEMME},
        year={2023},
        month={2},
        keywords={arima; steel price; forecasting; time series; arima-lstm},
        doi={10.4108/eai.18-11-2022.2326770}
    }
    
  • Haidi Wu
    Mingxun Li
    Kimhong Lim
    Cunrong Li
    Year: 2023
    Forecast of Steel Price on ARIMA-LSTM Model
    ICEMME
    EAI
    DOI: 10.4108/eai.18-11-2022.2326770
Haidi Wu1, Mingxun Li2, Kimhong Lim2, Cunrong Li3,*
  • 1: Industrial Engineering Department, School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan, China
  • 2: Mechanical Engineering Department, School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan, China
  • 3: Technical research and development Department, Suizhou Industrial Research Institute of Wuhan University of Technology, Wuhan University of Technology, Wuhan, China
*Contact email: 2832962632@qq.com

Abstract

Forecasting the price of steel is important for the manufacturing industry to make procurement plans and production plans. Price is affected by many factors, considering its time-series characteristics, this paper uses the ARIMA model to predict the linear part and LSTM to predict the non-linear residual part. Simulation results show that ARIMA-LSTM model has higher accuracy.