A Research on CO2 Emissions Intensity Prediction Based On the IOWA Combination Forecast Model

被引：0

作者：

Zhou Jianguo ^{[1
]}

Zhang Man ^{[2
]}

机构：

[1] North China Elect Power Univ, Sch Business Adm, Baoding 071000, Hebei, Peoples R China

[2] North China Elect Power Univ, Sch Econ & Management, Baoding 071000, Hebei, Peoples R China

来源：

PROCEEDINGS OF THE 10TH EURO-ASIA CONFERENCE ON ENVIRONMENT AND CORPORATE SOCIAL RESPONSIBILITY: TOURISM, SOCIETY AND EDUCATION SESSION, PT I | 2014年

关键词：

CO2 Emissions Intensity; Improved Gray Model; Generalized Neural Networks; IOWA Combination Forecasting Model;

D O I：

暂无

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

To solve the CO2 emissions intensity prediction problems in Hebei from China, the authors establish the IOWA combination forecasting model based on the improved gray and generalized neural networks. Taking data on the 2002-2011 Hebei CO2 emissions intensity as a basis, the authors use the contrasted combination forecasting model to forecast the data in the next five years. The results show that the predictions of the proposed combination model are more accurate. The model which is contrasted in this paper can be more effectively to solve CO2 emissions intensity forecasting problems.

引用

页码：159 / 167

页数：9

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