中国石油大学学报（自然科学版）2012，Vol.36Issue(1)：182-187,6.DOI:10.3969/j.issn.1673-5005.2012.01.033
基于支持向量回归机的中国碳排放预测模型
China's carbon emissions prediction model based on support vector regression
摘要
Abstract
Six influnce factors including population, urbanization rate, per capita GDP, added value proportion of service industry, per GDP energy consumption and coal consumption ratio were seleted as independent variables, and a model based on support vector regression ( SVR) was established for predicting carbon emissions of China. Using the data of carbon emissions and influence factors from the year 1980 to 2009 as samples, the SVR model with good learning and generalization ability was established through training and testing. According to the 12th five-year program, prediction values of influence facors under different situations were set, and the carbon emissions of China from the year 2010 to 2015 were predicted. The results show that China can appropriately reduce GDP growth speed and constantly optimize energy structure so as to achieve carbon reduction target efficiently.关键词
碳排放/支持向量回归机/预测模型Key words
carbon emissions/ support vector regression/ prediction model分类
资源环境引用本文复制引用
宋杰鲲..基于支持向量回归机的中国碳排放预测模型[J].中国石油大学学报（自然科学版）,2012,36(1):182-187,6.基金项目
山东省自然科学基金项目(ZR2011GQ004) （ZR2011GQ004）
山东省高校科研发展计划项目(J10WG94) （J10WG94）
中央高校基本科研业务费专项资金资助项目(11CX04034B,10CX04012B) （11CX04034B,10CX04012B）
教育部人文社科一般项目(10YJC630207) （10YJC630207）
