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Fuzzy Grey Model for Forecasting Non-homogeneous Exponential Sequence

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Abstract

Getting accurate results when GM (1, 1) model is used for fitting and predicting approximate non-homogeneous exponential sequence, is a challenge. We sought to address this issue by combining Grey Theory and Credibility Theory, to develop a fuzzy GM (1, 1) model (FGM), which introduces the double exponential fuzzy numbers and its membership function. The expectation of fuzzy variables for replacing the non-homogeneous exponential sequence was calculated by Credibility Theory, i.e. the homogeneous process. The novel method yields unbiased results when used in fitting and predicting the tight non-homogeneous exponential sequence. Finally, we use an empirical case and a numerical sequence case to illustrate the effectiveness, feasibility, and optimization of the FGM (1, 1) model.

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Acknowledgements

This work was supported by the Guangdong Province Philosophy and Social Sciences “Thirteenth Five-Year” Planning Discipline Co-construction Fund (no. GD17XGL02).

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Authors and Affiliations

  1. School of Computer Science, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, 528402, China

    Lei Cao

  2. School of Economics and Commerce, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, 528402, China

    Xiyu Cao

  3. School of Business Administration, Dongbei University of Finance and Economics, Dalian, 116025, China

    Qiangqiang Wang

  4. Lingnan College, Sun Yat-Sen University, Guangzhou, 510275, China

    Yiqiu Cao

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  1. Lei Cao
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  2. Xiyu Cao
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Correspondence to Qiangqiang Wang.

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Cao, L., Cao, X., Wang, Q. et al. Fuzzy Grey Model for Forecasting Non-homogeneous Exponential Sequence. Int. J. Fuzzy Syst. 24, 957–966 (2022). https://doi.org/10.1007/s40815-021-01179-7

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  • DOI: https://doi.org/10.1007/s40815-021-01179-7

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