Forecasting Natural Gas Consumption of China Using a Novel Grey Model
被引:20
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作者:
Zheng, Chengli
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机构:
Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R ChinaCent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China
Zheng, Chengli
[1
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Wu, Wen-Ze
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机构:
Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R ChinaCent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China
Wu, Wen-Ze
[1
]
Jiang, Jianming
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机构:
Baise Univ, Sch Math & Stat, Baise 533000, Peoples R ChinaCent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China
Jiang, Jianming
[2
]
Li, Qi
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机构:
Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R ChinaCent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China
Li, Qi
[1
]
机构:
[1] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China
[2] Baise Univ, Sch Math & Stat, Baise 533000, Peoples R China
As is known, natural gas consumption has been acted as an extremely important role in energy market of China, and this paper is to present a novel grey model which is based on the optimized nonhomogeneous grey model (ONGM (1,1)) in order to accurately predict natural gas consumption. This study begins with proving that prediction results are independent of the first entry of original series using the product theory of determinant; on this basis, it is a reliable approach by inserting an arbitrary number in front of the first entry of original series to extract messages, which has been proved that it is an appreciable approach to increase prediction accuracy of the traditional grey model in the earlier literature. An empirical example often appeared in testing for prediction accuracy of the grey model is utilized to demonstrate the effectiveness of the proposed model; the numerical results indicate that the proposed model has a better prediction performance than other commonly used grey models. Finally, the proposed model is applied to predict China's natural gas consumption from 2019 to 2023 in order to provide some valuable information for energy sectors and related enterprises.
机构:
Xian Univ Finance & Econ, Western Collaborat Innovat Res Ctr Energy Econ & R, Xian 710100, Peoples R ChinaXian Univ Finance & Econ, Western Collaborat Innovat Res Ctr Energy Econ & R, Xian 710100, Peoples R China
Wang, Huiping
Zhang, Zhun
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h-index: 0
机构:
Xian Univ Finance & Econ, Western Collaborat Innovat Res Ctr Energy Econ & R, Xian 710100, Peoples R ChinaXian Univ Finance & Econ, Western Collaborat Innovat Res Ctr Energy Econ & R, Xian 710100, Peoples R China
机构:
Southwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
Sichuan Normal Univ, Visual Comp & Virtual Real Key Lab Sichuan Prov, Chengdu 610068, Peoples R ChinaSouthwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
Wu, Wenqing
Ma, Xin
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h-index: 0
机构:
Southwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R ChinaSouthwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
Ma, Xin
Zeng, Bo
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机构:
Chongqing Technol & Business Univ, Coll Business Planning, Chongqing 400067, Peoples R ChinaSouthwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
Zeng, Bo
Lv, Wangyong
论文数: 0引用数: 0
h-index: 0
机构:
Sichuan Normal Univ, Visual Comp & Virtual Real Key Lab Sichuan Prov, Chengdu 610068, Peoples R China
Sichuan Normal Univ, Sch Math Sci, Chengdu 610068, Peoples R ChinaSouthwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
Lv, Wangyong
Wang, Yong
论文数: 0引用数: 0
h-index: 0
机构:
Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R China
Southwest Petr Univ, Sch Sci, Chengdu 610500, Peoples R ChinaSouthwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
Wang, Yong
Li, Wanpeng
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机构:
Manchester Metropolitan Univ, Sch Comp Math & Digital Technol, Manchester M1 5GD, Lancs, EnglandSouthwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China