Support Vector Regression Prediction Model for Peak Carbon Emissions of Hunan Expressway Infrastructure
The construction and operation of highway infrastructure is responsible for a large amount of CO2 emissions.The large amount of carbon dioxide emitted causes serious environmental pollution.In order to achieve sustainable development and green production,highways need to reduce carbon emissions.It is of guiding significance to clarify the current status of carbon emissions from transportation infrastructure,identify the influencing factors of carbon emissions,and predict future carbon emission trends.The purpose of this paper is to establish a model for scientifically predicting the carbon emissions of highway infrastructure.Through literature analysis and expert interviews,the influencing factors of carbon emissions of highway infrastructure were identified,including population,GDP per capita,fixed asset investment in transportation infrastructure,energy consumption per unit of transportation output value,and carbon emissions per unit of transportation energy consumption.Support vector regression is used to construct a prediction model of highway infrastructure carbon emissions.Taking Hunan Province as an example,the data from Hunan Province from 2003 to 2021 were selected as samples to train the model.Fourteen samples were randomly selected as the training set,and the model was trained on historical data.The remaining 5 samples form a test set to test the trained model.The results show that the mean square error of cross-validation of the training sample is 0.007011,the fitting regression effect of the predicted value and the real value of the model is good,and the correlation coefficients of the training set and the test set are 0.9869 and 0.9870,the model has good learning and generalization ability.Then,using scenario analysis and consulting relevant documents of the 14th Five-Year Plan of Hunan Province,the future values of the five influencing factors were predicted and analyzed,and finally three scenarios were set up:low-carbon,benchmark and ultra-low-carbon.The results show that under the baseline scenario,the peak of carbon emissions will occur in 2035,lagging behind the planned carbon peak process of Hunan Province.Even under the low-carbon scenario,the peak of carbon emissions will not be achieved until 2032.Only under the ultra-low-carbon scenario can the goal of carbon peak be achieved by 2030.This shows that Hunan Province still has a long way to go to achieve its carbon emission reduction target,and in order to achieve the goal of carbon peaking,the government should forecast the annual carbon emissions in advance and actively take carbon reduction measures to deal with it.The government can continue to promote carbon emission reduction by reducing energy consumption per unit of output value and carbon emissions per unit of energy consumption.The carbon emission prediction model of highway infrastructure constructs a carbon emission regression equation by selecting macro factors at the economic,demographic and energy technology levels,so as to improve the calculation efficiency of carbon emissions.Grasping the future carbon emission trend of expressway infrastructure can plan the construction and operation of expressways in advance,provide a scientific basis for formulating carbon emission reduction plans for transportation infrastructure,and achieve the goal of carbon neutrality.At the same time,it provides a reference scheme for other industries to conduct research on carbon emissions and carbon peaking,and realizes industry-wide carbon emission reduction.
support vector regression(SVR)carbon emission prediction modelhighway infrastructurecarbon peakinginfluencing factors
国家科技期刊平台
NSTL
万方数据
维普
