Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China
文献类型：期刊论文
| 作者 | Xiao, Yi2; Li, Keying2; Hu, Yi1; Xiao, Jin4; Wang, Shouyang3 |
| 刊名 | MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
 |
| 出版日期 | 2020-06-14 |
| 页码 | 19 |
| 关键词 | Natural gas consumption forecasting Emission reduction Deep learning STRIPAT model Gated recurrent unit model Bagging |
| ISSN号 | 1381-2386 |
| DOI | 10.1007/s11027-020-09918-1 |
| 英文摘要 | With the orderly advancement ofChina Energy Development Strategic Action Plan, clean energy has become a major trend in the energy market. As a major industry of clean energy, natural gas industry plans to consume at least 10% of the total primary energy by 2020. The energy structure will be improved in an orderly manner to achieve the goal of energy conservation, consumption reduction, and emission reduction. To achieve energy saving and emission reduction, and using clean energy effectively, accurate prediction of natural gas consumption is of great importance. Because of the many influencing factors affecting natural gas demand, this paper first utilizes STRIPAT to analyze the factors affecting natural gas consumption and then uses a deep learning ensemble approach to analyze and predict China's natural gas consumption. One is an advanced deep neural network model named gated recurrent unit model which is used to model the nonlinear and complex relationships of natural gas consumption with its factors. The other is a powerful ensemble method named bootstrap aggregation which generates multiple data sets for training a set of base models. Our approach combines the advantages of these two technologies to forecast the demand for China's natural gas market. In empirical research, our method has been tested by some competitive methods and has shown superiority. |
| 资助项目 | self-determined Research Funds of CCNU from the Colleges' Basic Research and Operation of MOE[CCNU19ZN024] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000540689300001 |
| 出版者 | SPRINGER |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/51651]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Xiao, Yi |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 2.Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 4.Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xiao, Yi,Li, Keying,Hu, Yi,et al. Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China[J]. MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE,2020:19. |
| APA | Xiao, Yi,Li, Keying,Hu, Yi,Xiao, Jin,&Wang, Shouyang.(2020).Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China.MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE,19. |
| MLA | Xiao, Yi,et al."Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China".MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE (2020):19. |
入库方式： OAI收割
来源：数学与系统科学研究院
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