Using fractional GM(1,1) model to predict the life of complex equipment
Abstract
Purpose
The purpose of this paper is to improve performance for predicting the life spans of complex equipment systems.
Design/methodology/approach
The gray system model with fractional order accumulation (FGM(1,1)) is used to predict the life spans of complex equipment systems using small samples.
Findings
FGM(1,1) yielded a lower mean absolute percentage error (MAPE) for an in-sample and a much lower MAPE for an out-of-sample forecast, which means that FGM(1,1) can predict memory processes.
Practical implications
FGM(1,1) can predict the life spans of other complex equipment.
Originality/value
FGM(1,1) yielded a lower MAPE for an in-sample and a much lower MAPE for out-of-sample forecasts, which means that FGM(1,1) can predict memory processes.
Keywords
Acknowledgements
The relevant research undertaken has been supported by the National Natural Science Foundation of China (No. 71401051), the Social Science Foundation of China’s Ministry of Education (No. 15YJA630017), the Program of the Research and Development Plan of Handan Science Technology (1034 201127) and the Project of the Social Science Foundation of China (No. 12 AZD102).
Citation
Wu, L. (2016), "Using fractional GM(1,1) model to predict the life of complex equipment", Grey Systems: Theory and Application, Vol. 6 No. 1, pp. 32-40. https://doi.org/10.1108/GS-07-2015-0034
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited