4.4 Article

Research on a novel fractional GM(α, n) model and its applications

Journal

GREY SYSTEMS-THEORY AND APPLICATION
Volume 9, Issue 3, Pages 356-373

Publisher

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/GS-11-2018-0052

Keywords

Genetic algorithm; Energy consumption; Forward difference method; Multivariate grey system; GM(a; n) model

Funding

  1. National Natural Science Foundation of China [71771033, 71571157, 11601357]
  2. Longshan academic talent research supporting programme of SWUST [17LZXY20]
  3. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University) [PLN 201710]
  4. applied basic research programme of science and technology commission foundation of Sichuan province [2017JY0159]
  5. V.C. AMP
  6. V.R. Key Lab of Sichuan Province [SCVCVR2018.08VS, SCVCVR2018.10VS]

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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(alpha, 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. Originality/value It is the first time to investigate the multivariate fractional grey GM(alpha, n) model, apply it to study the effects of China's economic growth and urbanization on energy consumption.

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