A new multivariable grey prediction model with structure compatibility

A new multivariable grey prediction model was proposed by adding a dependent variable lag term, a linear correction term and a random disturbance term to the traditional GM(1,N) model. It was theoretically proved that the new model can be completely compatible with the mainstream single variable and...

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Published in:	Applied Mathematical Modelling Vol. 75; p. 385
Main Authors:	Zeng, Bo, Duan, Huiming, Zhou, Yufeng
Format:	Journal Article
Language:	English
Published:	New York Elsevier BV 01.11.2019
Subjects:	Computer simulation Dependent variables Grey prediction
ISSN:	1088-8691, 0307-904X
Online Access:	Get full text
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Abstract	A new multivariable grey prediction model was proposed by adding a dependent variable lag term, a linear correction term and a random disturbance term to the traditional GM(1,N) model. It was theoretically proved that the new model can be completely compatible with the mainstream single variable and multivariable grey prediction models by adjusting and changing the model's parameters. To test the performance of the new model, three case studies were performed. The simulation and prediction results of the new model were compared with those of other grey prediction models. Results showed that the new model had evidently superior performance to other grey models, which confirms that the structure design of the new model is more reasonable than those of the other existing grey prediction models.
AbstractList	A new multivariable grey prediction model was proposed by adding a dependent variable lag term, a linear correction term and a random disturbance term to the traditional GM(1,N) model. It was theoretically proved that the new model can be completely compatible with the mainstream single variable and multivariable grey prediction models by adjusting and changing the model's parameters. To test the performance of the new model, three case studies were performed. The simulation and prediction results of the new model were compared with those of other grey prediction models. Results showed that the new model had evidently superior performance to other grey models, which confirms that the structure design of the new model is more reasonable than those of the other existing grey prediction models.
Author	Duan, Huiming Zeng, Bo Zhou, Yufeng
Author_xml	– sequence: 1 givenname: Bo surname: Zeng fullname: Zeng, Bo – sequence: 2 givenname: Huiming surname: Duan fullname: Duan, Huiming – sequence: 3 givenname: Yufeng surname: Zhou fullname: Zhou, Yufeng
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