The exponential grey forecasting model for CO₂ emissions in Taiwan Available to Purchase

– The purpose of this paper is to improve the forecasting efficiency of a grey model.

– The exponentially weighted moving average (EWMA) algorithm is proposed to modify background values for a new grey model optimization.

– The experimental results reveal that the proposed models (EGM, REGM) outperform traditional grey models.

– A genetic algorithm (GA) optimizer is used to select the optimal weights for the background values of the EGM(1,1) and REGM(1,1) forecast models. The results of the current study are very encouraging, as the empirical results show that the REGM(1,1) and EGM(1,1) models reduce the MAPE rates over the traditional GM(1,1) and RGM(1,1) models.