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A novel fractional order variable structure multivariable grey prediction model with optimal differential background-value coefficients and its performance comparison analysis

Chao Xia (Chongqing Technology and Business University, Chongqing, China)
Bo Zeng (Chongqing Technology and Business University, Chongqing, China)
Yingjie Yang (De Montfort University, Leicester, UK)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 9 February 2024

Issue publication date: 27 June 2024

62

Abstract

Purpose

Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.

Design/methodology/approach

A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.

Findings

The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.

Originality/value

This study has positive implications for enriching the method system of multivariable grey prediction model.

Keywords

Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos.72071023); the major project of science and technology research program of Chongqing Education Commission of China (Grant Nos.KJZD-M202300801); Chongqing Natural Science Foundation of China (Grant Nos. CSTB2023NSCQ-MSX0365 and CSTB2023NSCQ-MSX0380) and Chongqing Graduate Tutor Team Construction Project (Grant Nos. yds223006).

Citation

Xia, C., Zeng, B. and Yang, Y. (2024), "A novel fractional order variable structure multivariable grey prediction model with optimal differential background-value coefficients and its performance comparison analysis", Grey Systems: Theory and Application, Vol. 14 No. 3, pp. 429-450. https://doi.org/10.1108/GS-08-2023-0082

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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