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A Predictive Analysis of the Business Environment of Economies along the Belt and Road Using the Fractional-Order Grey Model

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  • Lingling Pei
  • Jun Liu
  • Lifeng Wu

Abstract

This paper determined the optimal order of FGM (1, 1) model through particle swarm optimization algorithm and combined with the World Bank business environment data to predict and analyze the business environment of economies along the Belt and Road. The empirical results show that the FGM (1, 1) model has a good predicting effect on the business environment. In terms of prediction accuracy, the FGM (1, 1) model based on particle swarm optimization algorithm to determine the optimal order is significantly better than the traditional GM (1, 1) model. The predict results show that the business environment level of economies along the Belt and Road will increase year by year from 2021 to 2022, but the overall level is still relatively low. The main innovation of this paper lies in the introduction of the fractional-order grey model into the predictive analysis of the business environment, which is of great significance to the extension and application of fractional-order models in management and economic systems.

Suggested Citation

  • Lingling Pei & Jun Liu & Lifeng Wu, 2021. "A Predictive Analysis of the Business Environment of Economies along the Belt and Road Using the Fractional-Order Grey Model," Journal of Mathematics, Hindawi, vol. 2021, pages 1-13, August.
    • Handle: RePEc:hin:jjmath:3153731
    DOI: 10.1155/2021/3153731
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    Cited by:

    1. Siyu Zhang & Liusan Wu & Ming Cheng & Dongqing Zhang, 2022. "Prediction of Whole Social Electricity Consumption in Jiangsu Province Based on Metabolic FGM (1, 1) Model," Mathematics, MDPI, vol. 10(11), pages 1-14, May.
    2. Lu, Hao & Fan, Yiwei & Jiao, Liudan & Wu, Ya, 2024. "Assessment and spatial effect of urban agglomeration business environments: A case study of two urban agglomerations in China," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

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