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Demand forecasting model of coal logistics based on drosophila-grey neural network

Author

Listed:
  • Shudong Wang

    (Anhui University of Science and Technology
    Huainan Union University)

  • Qinfeng Xing

    (Anhui University of Science and Technology)

  • Xiangqian Wang

    (Anhui University of Science and Technology)

  • Qian Wu

    (Anhui University of Science and Technology)

Abstract

The demanding forecast of coal logistics is the premise of integrating coal logistics resources and improving its efficiency. First, we considered the principles of index system construction and many other factors and chose GDP, average consumption, value added of the secondary industry, coal import and export volume, urban population quantity, coal production, total energy consumption, average annual rain PH, and coal consumption as a measure of indicators. Then, based on the idea of a combination model, the combination of grey model and BP neural network is selected, and FOA-GNNM is used to predict the coal consumption in China from 2018 to 2022, and the coal transportation volume in railway, highway and waterway is further calculated. The findings can help for better understanding of coal logistics, and then the following suggestions are proposed to improve its demanding forecast for China's future coal logistics operation arrangements, route planning and reserve system construction.

Suggested Citation

  • Shudong Wang & Qinfeng Xing & Xiangqian Wang & Qian Wu, 2023. "Demand forecasting model of coal logistics based on drosophila-grey neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(2), pages 807-815, April.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:2:d:10.1007_s13198-021-01586-x
    DOI: 10.1007/s13198-021-01586-x
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    References listed on IDEAS

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    1. Zaklan, Aleksandar & Cullmann, Astrid & Neumann, Anne & von Hirschhausen, Christian, 2012. "The globalization of steam coal markets and the role of logistics: An empirical analysis," Energy Economics, Elsevier, vol. 34(1), pages 105-116.
    2. Cattaneo, Cristina & Manera, Matteo & Scarpa, Elisa, 2011. "Industrial coal demand in China: A provincial analysis," Resource and Energy Economics, Elsevier, vol. 33(1), pages 12-35, January.
    3. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    4. Hongze Li & Sen Guo & Huiru Zhao & Chenbo Su & Bao Wang, 2012. "Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm," Energies, MDPI, vol. 5(11), pages 1-16, November.
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