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Development of the GM(1,1,⊗b) model with a trapezoidal possibility function and its application

Shuliang Li (Chongqing Jiaotong University, Chongqing, China) (Chongqing Technology and Business University, Chongqing, China)
Ke Gong (Chongqing Jiaotong University, Chongqing, China)
Bo Zeng (Rongzhi College of Chongqing Technology and Business University, Chongqing, China)
Wenhao Zhou (Chongqing Technology and Business University, Chongqing, China)
Zhouyi Zhang (Chongqing Jiaotong University, Chongqing, China)
Aixing Li (Chongqing Jiaotong University, Chongqing, China)
Li Zhang (Chongqing Jiaotong University, Chongqing, China)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 13 April 2021

Issue publication date: 28 February 2022

235

Abstract

Purpose

The purpose of this paper is to overcome the weakness of the traditional model, in which the grey action quantity is a real number and thus leads to a “unique solution” and to build the model with a trapezoidal possibility degree function.

Design/methodology/approach

Using the system input and output block diagram of the model, the interval grey action quantity is restored under the condition of insufficient system influencing factors, and the trapezoidal possibility degree function is formed. Based on that, a new model able to output non-unique solutions is constructed.

Findings

The model satisfies the non-unique solution principle of the grey theory under the condition of insufficient information. The model is compatible with the traditional model in structure and modelling results. The validity and practicability of the new model are verified by applying it in simulating the ecological environment water consumption in the Yangtze River basin.

Practical implications

In this study, the interval grey number form of grey action quantity is restored under the condition of insufficient system influencing factors, and the unique solution to the problem of the traditional model is solved. It is of great value in enriching the theoretical system of grey prediction models.

Social implications

Taking power consumption as an example, the accurate prediction of the future power consumption level is related to the utilization efficiency of the power infrastructure investment. If the prediction of the power consumption level is too low, it will lead to the insufficient construction of the power infrastructure and the frequent occurrence of “power shortage” in the power industry. If the prediction is too high, it will lead to excessive investment in the power infrastructure. As a result, the overall surplus of power supply will lead to relatively low operation efficiency. Therefore, building an appropriate model for the correct interval prediction is a better way to solve such problems. The model proposed in this study is an effective one to solve such problems.

Originality/value

A new grey prediction model with its interval grey action quantity based on the trapezoidal possibility degree function is proposed for the first time.

Keywords

Acknowledgements

Sincere thanks to editors and anonymous reviewers for their insightful comments and suggestions to improve the paper.

Data availability: The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of interest: The authors declare that there are no conflicts of interest regarding the publication of this paper.

Funding: The National Natural Science Foundation of China (71871034; 71771033; 72071023; 71801044); Chongqing Natural Science Foundation of China (cstc2020jcyj-msxmX0297; cstc2019jcyj-msxmX0003; cstc2019jcyj-msxmX0767); Chongqing Municipal Education Commission Science and Technology Research Project (KJQN201800805).

Citation

Li, S., Gong, K., Zeng, B., Zhou, W., Zhang, Z., Li, A. and Zhang, L. (2022), "Development of the GM(1,1,⊗b) model with a trapezoidal possibility function and its application", Grey Systems: Theory and Application, Vol. 12 No. 2, pp. 339-356. https://doi.org/10.1108/GS-11-2020-0145

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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