A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China

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  • Additional Information
    • Affiliation:
      a School of Science, Southwest University of Science and Technology, Mianyang, China
      b School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
      c School of Science, Southwest Petroleum University, Chengdu, China
      d College of Business Planning, Chongqing Technology and Business University, Chongqing, China
      e State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, China
    • Keywords:
      Energy consumption forecasting
      Energy economics
      Fractional grey model
      Grey wolf optimizer
      Five-year-plan
    • Abstract:
      Introduction of the fractional order accumulation has made significant contributions to the development of forecasting methods, and fractional grey models play a key role in such new methods. However, the fractional grey models may also be inaccurate in some cases as they do not consider the time delayed effect. To further improve the applicability of the existing fractional grey models, a novel fractional grey model called the fractional time delayed grey model is proposed in this paper. The essence of the fractional time delayed term is discussed, revealing that the fractional time delayed term is essentially a function between the polynomial functions with integer order, which can be more flexible to improve the modelling accuracy. The cutting-edge Grey Wolf Optimizer is introduced to find the optimal value of fractional order. Detailed modelling procedures, including the computational steps and the intelligent optimization algorithm, have been clearly presented. Four real world case studies are used to validate the effectiveness of the proposed model, in comparison with 8 existing grey models. Finally the proposed model is applied to forecast the coal and natural gas consumption of Chongqing China, the results show that the proposed model significantly outperforms the other 8 existing grey models.
    • ISSN:
      0360-5442
    • Accession Number:
      10.1016/j.energy.2019.04.096
    • Accession Number:
      S0360544219307297
    • Copyright:
      © 2019 Elsevier Ltd. All rights reserved.
  • Citations
    • ABNT:
      MA, X. et al. A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China. Energy, [s. l.], v. 178, p. 487–507, 2019. DOI 10.1016/j.energy.2019.04.096. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edselp&AN=S0360544219307297&custid=s8280428. Acesso em: 7 dez. 2019.
    • AMA:
      Ma X, Mei X, Wu W, Wu X, Zeng B. A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China. Energy. 2019;178:487-507. doi:10.1016/j.energy.2019.04.096.
    • APA:
      Ma, X., Mei, X., Wu, W., Wu, X., & Zeng, B. (2019). A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China. Energy, 178, 487–507. https://doi.org/10.1016/j.energy.2019.04.096
    • Chicago/Turabian: Author-Date:
      Ma, Xin, Xie Mei, Wenqing Wu, Xinxing Wu, and Bo Zeng. 2019. “A Novel Fractional Time Delayed Grey Model with Grey Wolf Optimizer and Its Applications in Forecasting the Natural Gas and Coal Consumption in Chongqing China.” Energy 178 (July): 487–507. doi:10.1016/j.energy.2019.04.096.
    • Harvard:
      Ma, X. et al. (2019) ‘A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China’, Energy, 178, pp. 487–507. doi: 10.1016/j.energy.2019.04.096.
    • Harvard: Australian:
      Ma, X, Mei, X, Wu, W, Wu, X & Zeng, B 2019, ‘A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China’, Energy, vol. 178, pp. 487–507, viewed 7 December 2019, .
    • MLA:
      Ma, Xin, et al. “A Novel Fractional Time Delayed Grey Model with Grey Wolf Optimizer and Its Applications in Forecasting the Natural Gas and Coal Consumption in Chongqing China.” Energy, vol. 178, July 2019, pp. 487–507. EBSCOhost, doi:10.1016/j.energy.2019.04.096.
    • Chicago/Turabian: Humanities:
      Ma, Xin, Xie Mei, Wenqing Wu, Xinxing Wu, and Bo Zeng. “A Novel Fractional Time Delayed Grey Model with Grey Wolf Optimizer and Its Applications in Forecasting the Natural Gas and Coal Consumption in Chongqing China.” Energy 178 (July 1, 2019): 487–507. doi:10.1016/j.energy.2019.04.096.
    • Vancouver/ICMJE:
      Ma X, Mei X, Wu W, Wu X, Zeng B. A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China. Energy [Internet]. 2019 Jul 1 [cited 2019 Dec 7];178:487–507. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edselp&AN=S0360544219307297&custid=s8280428