Study on Sales Forecast and Impact of New Energy Electric Vehicles Based on BP Neural Network

This paper presents a study on sales forecasts and influencing factors of new energy electric vehicles based on the BP neural network. In order to predict the development of China's new energy-electric vehicle industry, a predictive model is established using the BP neural network, which undergoes training at each stage. The error distribution histogram of the training results demonstrates the model's strong fitting effect, providing a reliable basis for future predictive analysis. Additionally, unit root testing (ADF testing) is conducted to assess the stationarity of the global new conventional energy vehicle sales time series from 2013 to 2023. Through impulse response analysis, the impact of new energy vehicle sales on traditional vehicle sales is observed, revealing early technological inadequacies and the gradual increase in market awareness. Furthermore, variance analysis quantifies the gradual growth impact of new energy vehicles on traditional vehicle sales.