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An innovative fractional grey system model and its application

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  • Wu, Wen-Ze
  • Xu, Jie
  • Xie, Wanli
  • Zhang, Tao

Abstract

In order to expand the applicability of the conventional fractional grey model, an innovative fractional grey model is proposed by the introduction of the innovative fractional accumulation. Three efforts are made in this study. First, the innovative fractional accumulation and its inverse operation are designed. Based on the innovative form, the parameter estimation and discrete time response of the novel model are given. In addition, the moth flame optimization algorithm is used to determine optimal hyper parameters for the novel model, and the rolling mechanism is used to enhance the prediction performance. To comprehensively confirm the forecasting ability of the proposed model, it is applied in three kinds of data with inverted U-shaped, W-shaped and oscillating features. The experimental results show the novel model is superior to all competitors in terms of level accuracy. Therefore, the novel model is considered a promising method for enhancing the existing fractional grey model.

Suggested Citation

  • Wu, Wen-Ze & Xu, Jie & Xie, Wanli & Zhang, Tao, 2025. "An innovative fractional grey system model and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 230(C), pages 68-79.
  • Handle: RePEc:eee:matcom:v:230:y:2025:i:c:p:68-79
    DOI: 10.1016/j.matcom.2024.11.003
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    1. Gao, Mingyun & Yang, Honglin & Xiao, Qinzi & Goh, Mark, 2022. "A novel method for carbon emission forecasting based on Gompertz's law and fractional grey model: Evidence from American industrial sector," Renewable Energy, Elsevier, vol. 181(C), pages 803-819.
    2. Chong Liu & Tongfei Lao & Wen-Ze Wu & Wanli Xie, 2021. "Application Of Optimized Fractional Grey Model-Based Variable Background Value To Predict Electricity Consumption," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(02), pages 1-15, March.
    3. He, Jing & Mao, Shuhua & Kang, Yuxiao, 2023. "Augmented fractional accumulation grey model and its application: Class ratio and restore error perspectives," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 220-247.
    4. Atef, Mohamed & Liu, Sifeng, 2024. "Four types of grey β-covering models and their applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 223(C), pages 108-129.
    5. Yin, Chen & Mao, Shuhua, 2023. "Fractional multivariate grey Bernoulli model combined with improved grey wolf algorithm: Application in short-term power load forecasting," Energy, Elsevier, vol. 269(C).
    6. Chen, Yan & Lifeng, Wu & Lianyi, Liu & Kai, Zhang, 2020. "Fractional Hausdorff grey model and its properties," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    7. Li, Shaohong & Wu, Na, 2021. "A new grey prediction model and its application in landslide displacement prediction," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    8. Gatabazi, P. & Mba, J.C. & Pindza, E., 2019. "Modeling cryptocurrencies transaction counts using variable-order Fractional Grey Lotka-Volterra dynamical system," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 283-290.
    9. Shaikh, Faheemullah & Ji, Qiang & Shaikh, Pervez Hameed & Mirjat, Nayyar Hussain & Uqaili, Muhammad Aslam, 2017. "Forecasting China’s natural gas demand based on optimised nonlinear grey models," Energy, Elsevier, vol. 140(P1), pages 941-951.
    10. 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).
    11. Zhou, Wenhao & Zeng, Bo & Wang, Jianzhou & Luo, Xiaoshuang & Liu, Xianzhou, 2021. "Forecasting Chinese carbon emissions using a novel grey rolling prediction model," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    12. Ding, Song & Zhang, Huahan, 2023. "Forecasting Chinese provincial CO2 emissions: A universal and robust new-information-based grey model," Energy Economics, Elsevier, vol. 121(C).
    13. Wu, Wen-Ze & Zeng, Liang & Liu, Chong & Xie, Wanli & Goh, Mark, 2022. "A time power-based grey model with conformable fractional derivative and its applications," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    14. Ye, Lili & Xie, Naiming & Boylan, John E. & Shang, Zhongju, 2024. "Forecasting seasonal demand for retail: A Fourier time-varying grey model," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1467-1485.
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