Combining a Genetic Algorithm and Support Vector Machine to Study the Factors Influencing CO 2 Emissions in Beijing with Scenario Analysis

Jinying Li, Binghua Zhang and Jianfeng Shi
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Jinying Li: Department of Economics and Management, North China Electric Power University, Baoding 071003, China
Binghua Zhang: Department of Economics and Management, North China Electric Power University, Baoding 071003, China
Jianfeng Shi: Department of Economics and Management, North China Electric Power University, Baoding 071003, China

Energies, 2017, vol. 10, issue 10, 1-17

Abstract: In recent years, Beijing has been facing serious environmental problems. As an important cause of environmental problems, a further study of the factors influencing CO 2 emissions in Beijing has important significance for the social and economic development of Beijing. In this paper, Cointegration and Granger causality test were proposed to select influencing factors of CO 2 emissions prediction in Beijing, the influencing factors with different leading lengths were checked as well, and the genetic algorithm (GA) was used to optimize the initial weight and threshold values of a support vector machine (SVM) and the new SVM optimized by GA (GA-SVM) was established to predict the CO 2 emissions of Beijing from 2016–2020 with scenario analysis. Through the comparison of 36 kinds of development scenarios, we found that economic growth, resident population growth and energy intensity enhancement were the major growth factors of carbon emissions, of which the contributions exceed 0.5% in all kinds of development scenarios. Finally, this paper put forward some reasonable policy recommendations for the control of CO 2 emissions.

Keywords: CO 2 emissions prediction; genetic algorithm; support vector machine; scenario analysis; influence factors (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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