Analysis of Greenhouse Gas Emissions in European Based on Hybrid Models

被引:0
|
作者
Yang, Hua [1 ]
Zhang, Jie [2 ]
Jiang, Feng [2 ]
机构
[1] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Hubei, Peoples R China
[2] Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan 430073, Hubei, Peoples R China
来源
2018 NINTH INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL AND INFORMATION PROCESSING (ICICIP) | 2018年
基金
中国国家自然科学基金;
关键词
Greenhouse gas emissions; clustering methods; model-based method;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The emission of greenhouse gas (GG) is a prime cause of global warming. But the emission reduction may lower economic growth rate. Since different countries have different industrial structure, the criteria of proper emission reduction is important for every country. In this paper we consider four GGs including carbon dioxide, nitrogen oxides, methane and nitrous oxide. Based on Gaussian hybrid model, we make clustering analysis for 31 European countries in 2017. The empirical analysis reveals that clustering membership becomes more distinct compared with k-means approach. In addition, the results show that 31 countries are grouped into four classes and Germany and France in the emissions of GGs are higher than others.
引用
收藏
页码:128 / 133
页数:6
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