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Forecast of Total Energy Consumption in Shandong Province Based on Grey BP Model

Received: 7 November 2018     Published: 8 November 2018
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Abstract

With the continuous increase of China's total energy consumption, we can find the rule and grasp its development trend from the change trend of energy consumption. In order to provide scientific basis for rational use of energy. In this paper,firstly, based on the data of total energy consumption of shandong province from 2007 to 2016, grey prediction model and BP neural network were used to predict total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted value of each year and the average relative error of the two models was 7.25% and 3.70% respectively. Secondly, on the basis of the grey prediction model, BP neural network was used to correct the predicted value of total energy in shandong province. Then, the grey BP modified model was used to obtain the total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted values of each year and the average relative error of the modified model was 2.04%. Finally, the total energy consumption of shandong province in 2018-2035 is predicted. The results show that the average relative error is small and the prediction effect is obvious. This shows that the grey BP model is effective in predicting total energy consumption.

Published in International Journal of Energy and Power Engineering (Volume 7, Issue 3)
DOI 10.11648/j.ijepe.20180703.13
Page(s) 40-46
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Grey Prediction, BP Neural Network, Grey BP Model, Total Energy Consumption

References
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  • APA Style

    Mengyao Mei, Lili Ma, Zhihong Liu, Zhongxian Zhu, Jianan Li, et al. (2018). Forecast of Total Energy Consumption in Shandong Province Based on Grey BP Model. International Journal of Energy and Power Engineering, 7(3), 40-46. https://doi.org/10.11648/j.ijepe.20180703.13

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    ACS Style

    Mengyao Mei; Lili Ma; Zhihong Liu; Zhongxian Zhu; Jianan Li, et al. Forecast of Total Energy Consumption in Shandong Province Based on Grey BP Model. Int. J. Energy Power Eng. 2018, 7(3), 40-46. doi: 10.11648/j.ijepe.20180703.13

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    AMA Style

    Mengyao Mei, Lili Ma, Zhihong Liu, Zhongxian Zhu, Jianan Li, et al. Forecast of Total Energy Consumption in Shandong Province Based on Grey BP Model. Int J Energy Power Eng. 2018;7(3):40-46. doi: 10.11648/j.ijepe.20180703.13

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  • @article{10.11648/j.ijepe.20180703.13,
      author = {Mengyao Mei and Lili Ma and Zhihong Liu and Zhongxian Zhu and Jianan Li and Xiaohan Fang},
      title = {Forecast of Total Energy Consumption in Shandong Province Based on Grey BP Model},
      journal = {International Journal of Energy and Power Engineering},
      volume = {7},
      number = {3},
      pages = {40-46},
      doi = {10.11648/j.ijepe.20180703.13},
      url = {https://doi.org/10.11648/j.ijepe.20180703.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20180703.13},
      abstract = {With the continuous increase of China's total energy consumption, we can find the rule and grasp its development trend from the change trend of energy consumption. In order to provide scientific basis for rational use of energy. In this paper,firstly, based on the data of total energy consumption of shandong province from 2007 to 2016, grey prediction model and BP neural network were used to predict total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted value of each year and the average relative error of the two models was 7.25% and 3.70% respectively. Secondly, on the basis of the grey prediction model, BP neural network was used to correct the predicted value of total energy in shandong province. Then, the grey BP modified model was used to obtain the total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted values of each year and the average relative error of the modified model was 2.04%. Finally, the total energy consumption of shandong province in 2018-2035 is predicted. The results show that the average relative error is small and the prediction effect is obvious. This shows that the grey BP model is effective in predicting total energy consumption.},
     year = {2018}
    }
    

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  • TY  - JOUR
    T1  - Forecast of Total Energy Consumption in Shandong Province Based on Grey BP Model
    AU  - Mengyao Mei
    AU  - Lili Ma
    AU  - Zhihong Liu
    AU  - Zhongxian Zhu
    AU  - Jianan Li
    AU  - Xiaohan Fang
    Y1  - 2018/11/08
    PY  - 2018
    N1  - https://doi.org/10.11648/j.ijepe.20180703.13
    DO  - 10.11648/j.ijepe.20180703.13
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
    SP  - 40
    EP  - 46
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20180703.13
    AB  - With the continuous increase of China's total energy consumption, we can find the rule and grasp its development trend from the change trend of energy consumption. In order to provide scientific basis for rational use of energy. In this paper,firstly, based on the data of total energy consumption of shandong province from 2007 to 2016, grey prediction model and BP neural network were used to predict total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted value of each year and the average relative error of the two models was 7.25% and 3.70% respectively. Secondly, on the basis of the grey prediction model, BP neural network was used to correct the predicted value of total energy in shandong province. Then, the grey BP modified model was used to obtain the total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted values of each year and the average relative error of the modified model was 2.04%. Finally, the total energy consumption of shandong province in 2018-2035 is predicted. The results show that the average relative error is small and the prediction effect is obvious. This shows that the grey BP model is effective in predicting total energy consumption.
    VL  - 7
    IS  - 3
    ER  - 

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Author Information
  • Department of Electrical Engineering, Rongcheng College, Harbin University of Science and Technology, Rongcheng, China

  • Department of Economic Management, Rongcheng Campus of Harbin University of Science and Technology, Rongcheng, China

  • Software Engineering Department, Rongcheng College, Harbin University of Science and Technology, Rongcheng, China

  • Software Engineering Department, Rongcheng College, Harbin University of Science and Technology, Rongcheng, China

  • Department of Electrical Engineering, Rongcheng College, Harbin University of Science and Technology, Rongcheng, China

  • Software Engineering Department, Rongcheng College, Harbin University of Science and Technology, Rongcheng, China

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