Using fractional order weakening buffer operator to forecast the main indices of online shopping in China
Grey Systems: Theory and Application
ISSN: 2043-9377
Article publication date: 5 December 2018
Issue publication date: 28 January 2019
Abstract
Purpose
The purpose of this paper is to predict the main economic indices of online shopping in China.
Design/methodology/approach
A fractional order weakening buffer operator (WBO) for the GM(1,1) model is put forward in order to solve the problem of limited nonlinear data. The order number of WBO can adjust in line with the scenario.
Findings
The experimental results indicate that the proposed method can consider the scenario and obtain more accurate forecasting results.
Originality/value
This study found that the slowdown of growth trend after the previous high speed expansion period will continue, and the online shopping sellers should make more efforts to develop potential consumers to increase its turnover.
Keywords
Acknowledgements
The relevant research studies in this paper are supported by the National Natural Science Foundation of China (No. 71871084, No. 71401051). The authors also thank the Project funded by China Postdoctoral Science Foundation (2018M630562) and the Project of Youth Top-notch Talents in Hebei Province.
Citation
Gao, X.H. and Wu, L. (2019), "Using fractional order weakening buffer operator to forecast the main indices of online shopping in China", Grey Systems: Theory and Application, Vol. 9 No. 1, pp. 128-140. https://doi.org/10.1108/GS-08-2018-0036
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited