Research on the Development Trend of China's New Energy Vehicle Based on ARIMA Model and Power Function Nonlinear Regression

This paper investigates the factors influencing the development of China's New Energy Vehicle (NEV) industry using an ARIMA model and power function nonlinear regression. A comprehensive dataset spanning 2013-2022 was collected and preprocessed, including technical, economic, convenience, and policy factors. The study employs entropy weight method for comprehensive evaluation and constructs a multiple linear regression model to analyze the impact of key factors. Correlation analysis and PCA visualization confirm the significant relationship between these factors and NEV development. The ARIMA and power function nonlinear regression models predict a robust growth in China's NEV industry over the next decade, with both models showing high accuracy in forecasting.

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Published
2025-03-17
DOI
https://doi.org/10.1109/eespe63401.2025.10987135
Primary Topic
Advanced Algorithms and Applications
Type
article
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article

Research on the Development Trend of China's New Energy Vehicle Based on ARIMA Model and Power Function Nonlinear Regression

Zhengyang Li
Advanced Algorithms and Applications
article

Research on the Development Trend of China's New Energy Vehicle Based on ARIMA Model and Power Function Nonlinear Regression

Zhengyang Li
article en

Abstract

This paper investigates the factors influencing the development of China's New Energy Vehicle (NEV) industry using an ARIMA model and power function nonlinear regression. A comprehensive dataset spanning 2013-2022 was collected and preprocessed, including technical, economic, convenience, and policy factors. The study employs entropy weight method for comprehensive evaluation and constructs a multiple linear regression model to analyze the impact of key factors. Correlation analysis and PCA visualization confirm the significant relationship between these factors and NEV development. The ARIMA and power function nonlinear regression models predict a robust growth in China's NEV industry over the next decade, with both models showing high accuracy in forecasting.

Fujian Normal University (CN)
Affordable and clean energy
Openalex Percentile: Top 89%
Advanced Algorithms and Applications
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