Forecasting annual electricity consumption in China by employing a conformable fractional grey model in opposite direction
被引:60
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作者:
Xie, Wanli
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机构:
Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R ChinaNanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China
Xie, Wanli
[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 ChinaNanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China
Wu, Wen-Ze
[2
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Liu, Chong
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Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R ChinaNanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China
Liu, Chong
[3
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Zhao, Jingjie
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Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R ChinaNanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China
Zhao, Jingjie
[1
]
机构:
[1] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China
[2] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China
[3] Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R China
Electric power makes a significant contribution to economic development. Predicting annual electricity consumption is becoming increasingly crucial for electric power utility planning and economic development. To address this problem, a novel conformable fractional grey model in opposite direction is presented to predict annual electricity consumption in China. Firstly, the computational formulas for the novel model are deduced by grey modelling method and the effectiveness of the novel model is proved by matrix perturbation theory. Secondly, the optimal parameters are determined by quantum inspired evolutionary algorithm. Thirdly, two empirical examples are taken to validate the prediction accuracy of the novel model. Finally, the proposed model is applied to predict electricity consumption of Beijing, Fujian and Shandong. The results show that the novel model is superior to other six competitive models. Besides, electricity consumption of these regions in next five years are predicted, which can well serve a benchmark research and provide a relatively reliable reference for economic and electric sectors. (C) 2020 Elsevier Ltd. All rights reserved.
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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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:
North China Elect Power Univ, Dept Econ & Management, Baoding 071003, Hebei, Peoples R ChinaNorth China Elect Power Univ, Dept Econ & Management, Baoding 071003, Hebei, Peoples R China
Meng, Ming
Fu, Yanan
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North China Elect Power Univ, Dept Econ & Management, Baoding 071003, Hebei, Peoples R ChinaNorth China Elect Power Univ, Dept Econ & Management, Baoding 071003, Hebei, Peoples R China
Fu, Yanan
Shi, Huifeng
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机构:
North China Elect Power Univ, Dept Math & Phys, Baoding 071003, Hebei, Peoples R ChinaNorth China Elect Power Univ, Dept Econ & Management, Baoding 071003, Hebei, Peoples R China
Shi, Huifeng
Wang, Xinfang
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机构:
Univ Manchester, Tyndall Ctr Climate Change Res, Manchester M13 9PL, Lancs, EnglandNorth China Elect Power Univ, Dept Econ & Management, Baoding 071003, Hebei, Peoples R China
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
Wu, Wen-Ze
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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
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
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