Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China

doi:10.1007/s11027-020-09918-1

CSpace

	Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China
	Xiao, Yi 1; Li, Keying 1; Hu, Yi 2; Xiao, Jin 3; Wang, Shouyang 4
	2020-06-14
发表期刊	MITIGATION AND ADAPTATION STRATEGIES FOR GLOBAL CHANGE
ISSN	1381-2386
页码	19
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.
关键词	Natural gas consumption forecasting Emission reduction Deep learning STRIPAT model Gated recurrent unit model Bagging
DOI	10.1007/s11027-020-09918-1
收录类别	SCI
语种	英语
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
WOS类目	Environmental Sciences
WOS记录号	WOS:000540689300001
出版者	SPRINGER
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/51652
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.Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China 2.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 3.Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, 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.