New Energy Vehicle Sales Forecasting Based on Weighted Optimization Models and LSTM

We will analyse the current situation of the development of new energy automobile industry, explore the new path of the development of new energy automobile industry, and make a reasonable prediction of the development prospect. Firstly, we will analyse the main factors affecting the development of new energy electric vehicles in China, and analyse them in five aspects: policy, price, macro, market and innovation, use principal component analysis to refine 35 indicators into five indicators, construct comprehensive score data based on the principal component scores, and carry out a comprehensive evaluation, and on the basis of which we will calculate the influence indexes of each factor, and explore these factors on the development of new energy electric vehicles in China. Then, grey prediction, regression prediction, and LSTM model are used to predict the development of China's new energy electric vehicles in the next 10 years, and the weighted prediction model is used to optimize the predicted values, and the accuracy of the prediction results is tested from the aspects of differentiation and standardization. And through these tests, we are able to assess the accuracy and applicability of the individual prediction models more comprehensively, and to provide a scientific and reasonable prediction basis for the future new energy automobile industry's development of the new energy vehicle industry in the future by providing a scientific and reasonable prediction basis.