Research on the Development Trend of New Energy Vehicles in China Based on BP Neural Network Modeling and Greedy Algorithm

The developing tendency of new energy cars in China is discussed. Firstly, four influencing indicators, namely, economy, policy, technology and after-sales service, were selected, and 11 years of data were collected and data preprocessing was carried out. The grey correlation model was set up to determine the size and order of the grey correlation coefficient, and the main factors influencing the development of NEV (new energy vehicles) and EV (electric vehicles) were identified. Then, the indicators were preliminarily analyzed using scatter plots. A linear regression model was established and solved using the least squares method to obtain the fitted functional relationships and predicted values. Moreover, a BP Neural Network forecast model and LSTM time series forecast model are built by MATLAB, which take the production and sales of NEV as the input variable, the training set of every influential index as the input variable, and the output of the new energy car in the coming decade as the output variable.