Prediction and Evaluation of the Impact of New Energy Electric Vehicles in China Based on Machine Learning

Considering the urgency of environmental issues and the importance of sustainable energy development, accelerating the development of China's new energy electric vehicle sector is an important decision. The study analyzed the expansion of Chinese new energy electric vehicle industry from 2002 to 2022 using entropy weighted TOPSIS method and gradient boosting regression method. The findings suggested that annual GDP and investment in renewable energy were two important contributors for the growth of new energy electric vehicles. Furthermore, this study compared six different machine learning models to determine which model was more appropriate for this study. The results showed that the gradient boosting regression model performed well in the forecasting task of this study. Moreover, this study quantitatively analyzed the impact of new energy electric vehicles on environmental improvement and traditional automobile industry. The analysis found that the introduction of new energy electric vehicles would significantly reduce regional environmental pollution index by 43.5% and lower the conventional vehicle development index by 12.99%. The findings showed that new energy electric vehicles had a great impact on the traditional automobile industry and made a significant contribution to improving the environment.