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.
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Acknowledgements
This study was supported by the National Natural Science Foundation of China (71701105), the Major Program of the National Social Science Fund of China (Grant No. 17ZDA092),the Humanities and Social Science Youth Fund Project of Ministry of Education of China (17YJC630182), Leverhulme Trust International Research Network project (IN-2014-020), the Royal Society International Exchanges 2017 Cost Share (China) (IEC\NSFC\170391), the Key Research Project of Philosophy and Social Sciences in Universities of Jiangsu Province (2018SJZDI111), and Jiangsu Provincial Government Scholarship for studying abroad(JS-2019-041).
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Xiong, P., Zou, X. & Yang, Y. The nonlinear time lag multivariable grey prediction model based on interval grey numbers and its application. Nat Hazards 107, 2517–2531 (2021). https://doi.org/10.1007/s11069-020-04476-w
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DOI: https://doi.org/10.1007/s11069-020-04476-w