Research on a novel fractional GM(α, n) model and its applications. Issue 3 (20th June 2019)

• Record Type: Journal Article
• Authors: Wu, Wenqing; Ma, Xin; Wang, Yong; Zhang, Yuanyuan; Zeng, Bo
• Is Part Of: Grey systems. Volume 9:Issue 3(2019)
• Page Start: 356
• Page End: 373
• Publication Date: 2019-06-20
• Subjects: Genetic algorithm -- Energy consumption -- Forward difference method -- Multivariate grey system -- GM(a, n) model; Cybernetics -- Periodicals; Systems engineering -- Periodicals; 003.5
• DOI: 10.1108/GS-11-2018-0052
• Languages: English
• ISSNs: 2043-9377

Abstract

Abstract : Purpose: The purpose of this paper is to develop a novel multivariate fractional grey model termed GM( a, n ) based on the classical GM(1, n ) model. The new model can provide accurate prediction with more freedom, and enrich the content of grey theory. Design/methodology/approach: The GM( α, n ) model is systematically studied by using the grey modelling technique and the forward difference method. The optimal fractional order a is computed by the genetic algorithm. Meanwhile, a stochastic testing scheme is presented to verify the accuracy of the new GM( a, n ) model. Findings: The recursive expressions of the time response function and the restored values of the presented model are deduced. The GM(1, n ), GM( a, 1) and GM(1, 1) models are special cases of the model. Computational results illustrate that the GM( a, n ) model provides accurate prediction. Research limitations/implications: The GM( a, n ) model is used to predict China's total energy consumption with the raw data from 2006 to 2016. The superiority of the GM( a, n ) model is more freedom and better modelling by fractional derivative, which implies its high potential to be used in energy field. Originality/value: It is the first time to investigate the multivariate fractional grey GM( α, n ) model, apply it to study the effects of China's economic growth and urbanization on energy consumption.