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China Total Energy Consumption Forecast with Optimized Continuous Conformable Fractional Grey Model

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  • Halis Bilgil
  • Ümmügülsüm Erdinç

Abstract

One of the methods used for forecasting of the time series is the fractional grey modeling approach. In this paper, the OCCFGM(1,1) model is utilized to forecasting of the total energy consumption data of China. The optimal values of α and r, which are fractional parameters in the model, are calculated using the Brute Force algorithm. Data collected from official sources from 2013 to 2022 are used to build the forecasting model, while data from 2013 to 2020 are employed to evaluate the accuracy at the model. The obtained results indicate that the OCCFGM(1,1) model exhibits superior forecasting performance compared to the other models under consideration.

Suggested Citation

  • Halis Bilgil & Ümmügülsüm Erdinç, 2024. "China Total Energy Consumption Forecast with Optimized Continuous Conformable Fractional Grey Model," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 12(3), pages 157-168, December.
    • Handle: RePEc:anm:alpnmr:v:12:y:2024:i:3:p:157-168
    DOI: https://doi.org/10.17093/alphanumeric.1447211
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    References listed on IDEAS

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    1. Ding, Song & Tao, Zui & Zhang, Huahan & Li, Yao, 2022. "Forecasting nuclear energy consumption in China and America: An optimized structure-adaptative grey model," Energy, Elsevier, vol. 239(PA).
    2. Xie, Wanli & Liu, Caixia & Wu, Wen-Ze & Li, Weidong & Liu, Chong, 2020. "Continuous grey model with conformable fractional derivative," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
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    More about this item

    Keywords

    Brute Force; Conformable fractional calculus; Energy Consumption; Fractional grey model; Least squares method; OCCFGM(1; 1) Model;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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