Using fractional GM(1,1) model to predict the life of complex equipment

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.