A new grey prediction model for forecasting the automobiles ownership in China

The average relative simulation and prediction percentage errors of the new model are only 0.092% and 3.023%, respectively. The simulation and prediction errors obtained from the classical GM(1,1) and the DGM(1,1) models are, respectively, 2.064% and 6.980% in the first case, and 1.942% and 7.360% in the second. The findings show that the GM(1,1,4) model has the best performance, which confirms the effectiveness of the structure improvement. The new model can enhance the smoothness of the background value and weaken the effects of extreme values in the raw sequence in the model’s performance. Therefore, the simulation and prediction performances of the GM(1,1,4) model are better than those of the traditional grey prediction models. The prediction show that the ownership for automobiles in China will grow rapidly in future. Findings could help the government in formulating adjustments to the industrial structures, and facilitate making rational yield plans for automobile firms.