Research on New Energy Vehicles Based on Multiple Linear Regression and Gray Prediction
DOI:
https://doi.org/10.54097/wg9x8y49Keywords:
New energy vehicles, conventional energy vehicles, gray prediction model, BP neural network, multiple linear regression Regression modelAbstract
The development of new energy vehicles has gradually become the focus of the global transportation field, and China has included the new energy vehicle industry in the seven strategic emerging industries, but at this stage there are still many factors affecting the development of China's new energy automobile industry. This paper collects the main index data of the old and emerging enterprises, and establishes a gray prediction model based on the analysis of the development level of the two kinds of enterprises in each year, predicts the indexes in turn, and trains the BP neural network model with the original index data. Collect the sales of new energy electric vehicles and traditional energy vehicles, draw the sales comparison chart and market share chart, so as to conclude that the traditional vehicles currently dominate the market, and secondly draw the scatter plot of the two found that the relationship between the two is similar to a hyperbola, and establish a multivariate linear regression model.
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