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The nonlinear time lag multivariable grey prediction model based on interval grey numbers and its application

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  • Pingping Xiong

    (Nanjing University of Information Science and Technology
    Nanjing University of Information Science and Technology)

  • Xia Zou

    (Nanjing University of Information Science and Technology
    Nanjing University of Information Science and Technology)

  • Yingjie Yang

    (De Montfort University)

Abstract

The linear relationship of the original grey prediction model is too single, and the original grey prediction model does not consider the time delay of the effect of the current input parameters on the output parameters. In order to solve these problems, the interval grey number sequence is taken as the modelling sequence of the model, and the nonlinear parameter γ and the time-delay parameter τ are introduced into the multivariate grey prediction model, so as to construct the nonlinear time-delay multivariable grey prediction model for interval grey number. In view of the uncertain characteristics of the smog index data, this paper applies the improved model to the simulation and prediction of the smog index data. Compared with the original model, the results show that the prediction effect of the model proposed in this paper is superior to the original model in terms of its effectiveness and feasibility.

Suggested Citation

  • Pingping Xiong & Xia Zou & Yingjie Yang, 2021. "The nonlinear time lag multivariable grey prediction model based on interval grey numbers and its application," 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(3), pages 2517-2531, July.
    • Handle: RePEc:spr:nathaz:v:107:y:2021:i:3:d:10.1007_s11069-020-04476-w
    DOI: 10.1007/s11069-020-04476-w
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