Modeling and Estimation of CO2 Emissions in China Based on Artificial Intelligence
文献类型：期刊论文
| 作者 | Wang, Pan5; Zhong, Yangyang2,3,4; Yao, Zhenan1 |
| 刊名 | COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
 |
| 出版日期 | 2022-07-07 |
| 卷号 | 2022页码:14 |
| ISSN号 | 1687-5265 |
| DOI | 10.1155/2022/6822467 |
| 通讯作者 | Zhong, Yangyang(zhyy168@ecut.edu.cn) |
| 英文摘要 | Since China's reform and opening up, the social economy has achieved rapid development, followed by a sharp increase in carbon dioxide (CO2) emissions. Therefore, at the 75th United Nations General Assembly, China proposed to achieve carbon peaking by 2030 and carbon neutrality by 2060. The research work on advance forecasting of CO2 emissions is essential to achieve the above-mentioned carbon peaking and carbon neutrality goals in China. In order to achieve accurate prediction of CO2 emissions, this study establishes a hybrid intelligent algorithm model suitable for CO2 emissions prediction based on China's CO2 emissions and related socioeconomic indicator data from 1971 to 2017. The hyperparameters of Least Squares Support Vector Regression (LSSVR) are optimized by the Adaptive Artificial Bee Colony (AABC) algorithm to build a high-performance hybrid intelligence model. The research results show that the hybrid intelligent algorithm model designed in this paper has stronger robustness and accuracy with relative error almost within +/- 5% in the advance prediction of CO2 emissions. The modeling scheme proposed in this study can not only provide strong support for the Chinese government and industry departments to formulate policies related to the carbon peaking and carbon neutrality goals, but also can be extended to the research of other socioeconomic-related issues. |
| WOS关键词 | CARBON-DIOXIDE EMISSIONS ; ENERGY-CONSUMPTION ; ECONOMIC-GROWTH ; EFFICIENCY ; URBANIZATION ; METHODOLOGY ; PERFORMANCE ; PROVINCE ; TOURISM ; TRADE |
| 资助项目 | Scientific Research Foundation of East China University of Technology[DHBK2019305] ; State Key Laboratory of Palaeobiology and Stratigraphy (Nanjing Institute of Geology and Palaeontology, CAS)[203125] |
| WOS研究方向 | Mathematical & Computational Biology ; Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:000830839300010 |
| 出版者 | HINDAWI LTD |
| 资助机构 | Scientific Research Foundation of East China University of Technology ; State Key Laboratory of Palaeobiology and Stratigraphy (Nanjing Institute of Geology and Palaeontology, CAS) |
| 源URL | [http://ir.nigpas.ac.cn/handle/332004/41079]  |
| 专题 | 中国科学院南京地质古生物研究所 |
| 通讯作者 | Zhong, Yangyang |
| 作者单位 | 1.East China Univ Technol, Engn Res Ctr Seism Disaster Prevent & Engn Geol Di, Nanchang 330013, Jiangxi, Peoples R China 2.Chinese Acad Sci, Nanjing Inst Geol & Palaeontol, State Key Lab Palaeobiol & Stratig, Nanjing 210008, Jiangsu, Peoples R China 3.East China Univ Technol, Jiangxi Engn Lab Radioact Geosci & Big Data Techno, Nanchang 330013, Jiangxi, Peoples R China 4.East China Univ Technol, Sch Informat Engn, Nanchang 330013, Jiangxi, Peoples R China 5.East China Univ Technol, State Key Lab Nucl Resources & Environm, Nanchang 330013, Jiangxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Pan,Zhong, Yangyang,Yao, Zhenan. Modeling and Estimation of CO2 Emissions in China Based on Artificial Intelligence[J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2022,2022:14. |
| APA | Wang, Pan,Zhong, Yangyang,&Yao, Zhenan.(2022).Modeling and Estimation of CO2 Emissions in China Based on Artificial Intelligence.COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2022,14. |
| MLA | Wang, Pan,et al."Modeling and Estimation of CO2 Emissions in China Based on Artificial Intelligence".COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022(2022):14. |
入库方式： OAI收割
来源：南京地质古生物研究所
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