Title
Fdgm(1,1) Model Based On Unified Fractional Grey Generation Operator
Abstract
Purpose The purpose of this paper is to unify the expression of fractional grey accumulating generation operator and the reducing generation operator, and build the FDGM(1,1) model with the unified fractional grey generation operator. Design/methodology/approach By systematically studying the properties of the fractional accumulating operator and the reducing operator, and analyzing the sensitivity of the order value, a unified expression of the fractional operators is given. The FDGM(1,1) model with the unified fractional grey generation operator is established. The relationship between the order value and the modeling error distribution is studied. Findings The expression of the fractional accumulating generation operator and the reducing generation operator can be unified to a simple expression. For -1<r < 1, the fractional grey generation operator satisfies the principle of new information priority. The DGM(1,1) model is a special case of the FDGM(1,1) model with r = 1. Research limitations/implications The sensitivity of the unified operator is verified through random numerical simulation method, and the theoretical proof was not yet possible. Practical implications The FDGM(1,1) model has a higher modeling accuracy and modeling adaptability than the DGM(1,1) by optimizing the order. Originality/value The expression of the fractional accumulating generation operator and the reducing generation operator is firstly unified. The FDGM(1,1) model with the unified fractional grey generation operator is firstly established. The unification of the fractional accumulating operator and the reducing operator improved the theoretical basis of grey generation operator.
Year
DOI
Venue
2021
10.1108/GS-07-2020-0093
GREY SYSTEMS-THEORY AND APPLICATION
Keywords
DocType
Volume
Grey prediction model, Fractional operator, DGM(1, 1)
Journal
11
Issue
ISSN
Citations 
3
2043-9377
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Wei Meng100.34
Qian Li200.34
Bo Zeng37613.74
Yingjie Yang410.69