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

Date

2021-01-02

Advisors

Journal Title

Journal ISSN

ISSN

0921-030X

Volume Title

Publisher

Springer

Type

Article

Peer reviewed

Yes

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.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Open access article.

Keywords

gray system, interval gray number, nonlinear, time lag, smog

Citation

Xiong, P., Zou, X. and Yang, Y. (2021) The nonlinear time lag multivariable grey prediction model based on interval grey numbers and its application. Natural Hazards, 107, pp.2517–2531.

Rights

Research Institute