• DocumentCode
    2470908
  • Title

    Supply and demand prediction of Shandong coal resources based on mathematical statistics model

  • Author

    Xiao, Xingyuan ; Zhang, Hongri ; Jiang, Tao ; Yang, Li

  • Author_Institution
    Geomatics Coll., Shandong Univ. of Sci. & Technol., Qingdao, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    6399
  • Lastpage
    6402
  • Abstract
    Shandong is one of the important energy resources base in the whole nation. It accounts for 6% of coal output, stands 5th in China and the energy resources consumption stands the first. With the rapid development of economic society and urbanization, there is a great amount of coal resources demand. The balance of coal supply can provide technique support to energy resource development plan of Shandong, and power to economic society development. Based on the main problems in coal exploration and utilization, we accords to the coal output and consumption in these two decades, and takes GM (1,1) model and trendline model to predict the coal demand and supply in the next decade. The result shows that gap of coal supply and demand in Shandong is growing gradually and the dependence on the outside world of coal consumption is rising continuously, which causes the serious imbalance between supply and demand.
  • Keywords
    grey systems; industrial economics; mining industry; resource allocation; statistics; supply and demand; GM (1,1) model; Shandong coal resource; coal exploration; coal supply; coal utilization; economic society; mathematical statistics model; supply-and-demand prediction; trendline model; urbanization; Coal; Coal mining; Mathematical model; Predictive models; Supply and demand; GM (1,1) model; Shandong Province; coal resources; supply and demand prediction; trendline model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-9172-8
  • Type

    conf

  • DOI
    10.1109/RSETE.2011.5965821
  • Filename
    5965821