• DocumentCode
    2418978
  • Title

    Coal Requirement Prediction Using BP Neural Network

  • Author

    Xuxin ; Xu Lihong

  • Author_Institution
    Manage. Dept., Univ. of Shanghai Sci. & Technol., Shanghai, China
  • fYear
    2010
  • fDate
    7-9 May 2010
  • Firstpage
    3815
  • Lastpage
    3818
  • Abstract
    Coal is one of the most important main energy-consuming resources in our society. It is important to forecast the coal requirement with high accuracy. BP neural network forecasting model has the typical of self-learning and self-adaptation. It is often used in these systems that are difficult to create accurate mathematical model. The factors such as the trend of the industrial coal, the rate of increased GDP, rice index and the proportion in the energy-consuming of coal are considered in this paper. We use improved BP model to predict and simulate in MATLAB. It proves that this prediction has better application.
  • Keywords
    backpropagation; coal; demand forecasting; forecasting theory; neural nets; BP neural network; Matlab; coal; forecasting model; requirement prediction; self-adaptation; self-learning; Artificial neural networks; Economic indicators; Finance; Indexes; MATLAB; Mathematical model; Predictive models; BP neural network; MATLAB; coal demand prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Business and E-Government (ICEE), 2010 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-0-7695-3997-3
  • Type

    conf

  • DOI
    10.1109/ICEE.2010.956
  • Filename
    5591798