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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.
© Emerald Group Publishing Limited
2016
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