• DocumentCode
    2470803
  • Title

    Study on the prediction of coal ash based on image recognition and BP neural network

  • Author

    Ling, Xiangyang ; Wang, Yuling

  • Author_Institution
    Sch. of Chem. Eng. & Technol., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    6378
  • Lastpage
    6380
  • Abstract
    Based on image recognition of coal particles, taking red average, green average, blue average, brightness average, saturation average, chroma average, mean value of gray scale, contrast ratio, and correlation as the input vectors, and using the BP neural network, this paper study on the prediction of coal ash. After establishing the network and training the experimental data in it, the network is stimulated. The result shows that the network has better prediction accuracy.
  • Keywords
    brightness; coal ash; image recognition; neural nets; physics computing; BP neural network; blue average; brightness average; chroma average; coal ash; coal particles; contrast ratio; gray scale; green average; image recognition; red average; saturation average; Artificial neural networks; Ash; Coal; MATLAB; Measurement uncertainty; Neurons; Training; BP neural network; average; coal ash; image recognition; prediction; stimulation;
  • 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.2011.5965816
  • Filename
    5965816