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Continuous grey model with conformable fractional derivative

Author

Listed:
  • Xie, Wanli
  • Liu, Caixia
  • Wu, Wen-Ze
  • Li, Weidong
  • Liu, Chong

Abstract

Fractional-order grey models have received more attention owing to superiority to integer-order ones in terms of the prediction performance. In this paper, to further improve the performance of grey-based model, a new method based on conformable fractional derivative, the continuous conformable fractional grey model (denoted as CCFGM(1,1) for short), is proposed. In comparison with the traditional fractional-order grey models, the novel model possesses the simpler computation procedure. The numerical results of two real cases show that the prediction performance of the novel model is superior to other competitive models and therefore, it is proved that this model effectively brings forth the improvement of the existing fractional-order grey models.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:chsofr:v:139:y:2020:i:c:s0960077920306810
    DOI: 10.1016/j.chaos.2020.110285
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    References listed on IDEAS

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    Cited by:

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    2. Anatoliy Martynyuk & Gani Stamov & Ivanka Stamova & Ekaterina Gospodinova, 2023. "Formulation of Impulsive Ecological Systems Using the Conformable Calculus Approach: Qualitative Analysis," Mathematics, MDPI, vol. 11(10), pages 1-15, May.
    3. Yang, Zhongsen & Wang, Yong & Zhou, Ying & Wang, Li & Ye, Lingling & Luo, Yongxian, 2023. "Forecasting China's electricity generation using a novel structural adaptive discrete grey Bernoulli model," Energy, Elsevier, vol. 278(C).
    4. Jianzhou Wang & Pei Du, 2021. "Quarterly PM2.5 prediction using a novel seasonal grey model and its further application in health effects and economic loss assessment: evidences from Shanghai and Tianjin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(1), pages 889-909, May.
    5. Yang, Yang & Wang, Xiuqin, 2022. "A novel modified conformable fractional grey time-delay model for power generation prediction," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    6. Zhenguo Xu & Wanli Xie & Caixia Liu, 2023. "An Optimized Fractional Nonlinear Grey System Model and Its Application in the Prediction of the Development Scale of Junior Secondary Schools in China," Sustainability, MDPI, vol. 15(4), pages 1-12, February.

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