Abstract

In the current global context, it is crucial to forecast trends in new energy electric vehicles. In this study, we used three forecasting models, namely, grey prediction, time series analysis and BP neural network, and compared and evaluated the forecasting effects of the models, which showed that the evaluation indexes of BP neural network model were much better than those of the other models, in which the coefficient of determination (R2) reaches 0.9929, which indicates that the prediction of BP neural network model is the most effective. The results showed that the new energy electric vehicle industry in China as a whole showed a steady and benign development trend.

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