典型文献
Quantitative Analysis and Prediction of China's Natural Gas Consumption in Different Sectors Based on Bayesian Network
文献摘要：
In view of the heterogeneity of natural gas consumption in different sectors in China,this paper utilizes Bayesian network(BN)to study the driving factors of natural gas consumption in power generation,chemical and industrial fuel sectors.Combined with Bayesian model averaging(BMA)and scenario analysis,the gas consumption of the three sectors is predicted.The results show that the expansion of urbanization will promote the gas consumption of power generation.The optimization of industrial structure and the increase of industrial gas consumption will enhance the gas consumption of chemical sector.The decrease of energy intensity and the increase of gas consumption for power generation will promote the gas consumption of industrial fuel.Moreover,the direct influencing factors of gas price are urbanization,energy structure and energy intensity.The direct influencing factors of environmental governance intensity are gas price,urbanization,industrial structure,energy intensity and energy structure.In 2025,under the high development scenario,China's gas consumption for power generation,chemical and industrial fuel sectors will be 66.034,36.552 and 109.414 billion cubic meters respectively.From 2021 to 2025,the average annual growth rates of gas consumption of the three sectors will be 4.82％,2.18％and 4.43％respectively.
文献关键词：
中图分类号：
作者姓名：
Jian CHAI;Yabo WANG;Zhaohao WEI;Huiting SHI;Xiaokong ZHANG;Xuejun ZHANG
作者机构：
School of Economics and Management,Xidian University,Xi'an 710126,China;School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190,China
文献出处：
引用格式：
[1]Jian CHAI;Yabo WANG;Zhaohao WEI;Huiting SHI;Xiaokong ZHANG;Xuejun ZHANG-.Quantitative Analysis and Prediction of China's Natural Gas Consumption in Different Sectors Based on Bayesian Network)[J].系统科学与信息学报（英文版）,2022(04):338-353
A类：
Sectors
B类：
Quantitative,Analysis,Prediction,China,Natural,Gas,Consumption,Different,Based,Bayesian,Network,In,view,heterogeneity,natural,gas,consumption,different,sectors,this,paper,utilizes,network,BN,study,driving,factors,power,generation,chemical,industrial,fuel,Combined,model,averaging,BMA,scenario,analysis,three,predicted,results,show,that,expansion,urbanization,will,promote,optimization,structure,increase,enhance,decrease,energy,intensity,Moreover,direct,influencing,price,are,environmental,governance,under,high,development,be,billion,cubic,meters,respectively,From,average,annual,growth,rates
AB值：
0.424901
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