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Abstract
In recent years, under a series of policy shocks, the production and sales of new
energy vehicles in China show the characteristics of trend mutation and non-smoothness.
In order to forecast the production and sales of new energy vehicles in China, an
optimised grey buffer operator is proposed by introducing accumulation and translation
transformations. Meanwhile, a genetic algorithm is employed to ascertain its optimum
parameters. Forecasting results indicate that the optimised buffer operator can significantly
improve the adaptability of the grey model to the production and sales data of new
energy vehicles in China, and exhibits much higher prediction accuracy than those
of the classical buffer operator and grey model. Besides, the prediction results show
that the production and sales of China's new energy vehicles will continue to grow
from 2018 to 2020, with an average annual growth rate of 27.53% and 30.49%, respectively.