Predicting China's energy consumption using a novel grey Riccati model

被引:59
|
作者
Wu, Wenqing [1 ,2 ]
Ma, Xin [1 ,3 ]
Wang, Yong [3 ,4 ]
Cai, Wei [5 ]
Zeng, Bo [6 ]
机构
[1] Southwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
[2] Sichuan Normal Univ, Visual Comp & Virtual Real Key Lab Sichuan Prov, Chengdu 610068, Peoples R China
[3] Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Peoples R China
[4] Southwest Petr Univ, Sch Sci, Chengdu 610500, Peoples R China
[5] Southwest Univ, Coll Engn & Technol, Chongqing 400715, Peoples R China
[6] Chongqing Technol & Business Univ, Coll Business Planning, Chongqing 400067, Peoples R China
基金
中国国家自然科学基金;
关键词
Grey Riccati model; Energy consumption; Simulated annealing algorithm; Genetic algorithm; Optimized parameter; FORECASTING-MODEL; BASS MODEL; OPTIMIZATION; ALGORITHMS; GROWTH;
D O I
10.1016/j.asoc.2020.106555
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper studies the China's oil consumption and the China's nuclear energy consumption by a grey Riccati model. The newly developed model is analysed by the trapezoidal formula of definite integrals, the theory of ordinary differential equations and the grey technique. And some special cases including the GM(1,1) model, the grey Verhulst model and the grey Bass model are all discussed. Meanwhile, the hybrid of the simulated annealing algorithm and the genetic algorithm is utilized to search optimal background values. Further, the performance of the new model is verified through some experiments. Finally, the model is applied to study China's energy consumption with original sequences from 2001 to 2018 claimed by British Petroleum Statistical Review of World Energy 2019, and the results show that the new model can obtain competitive results and better than other comparative models. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页数:11
相关论文
共 50 条
  • [21] A new multivariate grey prediction model for forecasting China’s regional energy consumption
    Geng Wu
    Yi-Chung Hu
    Yu-Jing Chiu
    Shu-Ju Tsao
    Environment, Development and Sustainability, 2023, 25 : 4173 - 4193
  • [22] A novel grey power-Markov model for the prediction of China’s electricity consumption
    Liqin Sun
    Youlong Yang
    Tong Ning
    Jiadi Zhu
    Environmental Science and Pollution Research, 2022, 29 : 21717 - 21738
  • [23] A novel grey power-Markov model for the prediction of China's electricity consumption
    Sun, Liqin
    Yang, Youlong
    Ning, Tong
    Zhu, Jiadi
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (15) : 21717 - 21738
  • [24] Forecasting China's renewable energy consumption using a novel dynamic fractional-order discrete grey multi-power model
    Xia, Lin
    Ren, Youyang
    Wang, Yuhong
    Pan, Yangyang
    Fu, Yiyang
    RENEWABLE ENERGY, 2024, 233
  • [25] Forecasting China's energy production and consumption based on a novel structural adaptive Caputo fractional grey prediction model
    Wang, Yong
    Yang, Zhongsen
    Wang, Li
    Ma, Xin
    Wu, Wenqing
    Ye, Lingling
    Zhou, Ying
    Luo, Yongxian
    ENERGY, 2022, 259
  • [26] Forecasting the hydroelectricity consumption of China by using a novel unbiased nonlinear grey Bernoulli model
    Zheng, Chengli
    Wu, Wen-Ze
    Xie, Wanli
    Li, Qi
    Zhang, Tao
    JOURNAL OF CLEANER PRODUCTION, 2021, 278 (278)
  • [27] Forecasting short-term renewable energy consumption of China using a novel fractional nonlinear grey Bernoulli model
    Wu, Wenqing
    Ma, Xin
    Zeng, Bo
    Wang, Yong
    Cai, Wei
    RENEWABLE ENERGY, 2019, 140 : 70 - 87
  • [28] A novel grey seasonal model based on cycle accumulation generation for forecasting energy consumption in China
    Zhou, Weijie
    Pan, Jiao
    Tao, Huihui
    Ding, Song
    Chen, Li
    Zhao, Xiaoke
    COMPUTERS & INDUSTRIAL ENGINEERING, 2022, 163
  • [29] An improved multivariable grey Riccati-Bernoulli model and its application in energy consumption prediction
    Meng, Dun
    Dang, Yaoguo
    Wang, Junjie
    Zhou, Huimin
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2025,
  • [30] A Novel Logistic Multivariate Grey Prediction Model for Energy Consumption: A case study of China Coal
    Chen, Sihao
    Liu, Yongshan
    Duan, Huiming
    JOURNAL OF GREY SYSTEM, 2023, 35 (04): : 132 - 153