The accumulation of carbon dioxide will not only cause global warming but also cause a series of catastrophic consequences and cause irreversible damage to the earth's ecology. The prediction of carbon dioxide emissions from light-duty vehicles can provide decision-making support for consumers when purchasing cars and is beneficial to consumers in purchasing environmentally friendly cars. This paper constructs a vehicle carbon dioxide emission model based on a multiple linear regression model, using the four indicators of vehicle engine size, vehicle fuel consumption, Hwy (L/100km), and Comb (L/100km) as output variables. The quantity is the predictor variable. The correlation coefficient of this study is 0.9675. The regression equation of this linear regression model is Y=22.2344+2.7157X1+32.9843X2+26.6259X3-39.1429X4. The order of impact of the four indicators studied on carbon emissions is Comb (L/100km), vehicle fuel consumption, Hwy (L/100km), and vehicle engine size. The determination of carbon emissions of specific models of new light vehicles can refer to the multiple linear regression model proposed in this study.
No takes yet. Share an insight, caveat, or question.
Zikun Chen (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: