Harnessing Regression Analysis and Machine Learning to Unveil the Market Dynamics and Environmental Impact of New Energy Vehicles
DOI:
https://doi.org/10.54097/k2ggwv44Keywords:
Logistic regression model, 2 test, Multicollinearity analysis.Abstract
This study leverages regression analysis and machine learning algorithms to systematically investigate the growth patterns of the global New Energy Vehicle (NEV) market, evaluate the effects of international policy frameworks on NEVs, and quantify the environmental advantages of NEVs in urban settings. Through the analysis of worldwide market data, case studies on international policies, and urban air quality metrics, this research delineates the pivotal contributions of NEVs to mitigating urban pollution and advancing environmental sustainability. The findings provide empirical evidence and strategic recommendations for policymakers, the automotive industry, and environmental organizations, aimed at promoting the sustainable development of the global NEV market.
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