• DocumentCode
    2172811
  • Title

    Intelligent classification strategy for flammable-gases base on BP neural network

  • Author

    Zhang, Chenchen ; Qi, Jianling

  • Author_Institution
    Dept. of Inf. Eng., China Univ. Of Geosci. Beijng, Beijing, China
  • fYear
    2011
  • fDate
    9-11 Sept. 2011
  • Firstpage
    3776
  • Lastpage
    3779
  • Abstract
    In the chemical and industrial field, the technology of detecting flammable or poisonous gases had always been important for product-safety control. Since the most of the work environment is complex and the gas always is complicated mixture, the precision of detection is rather low. IF the advanced pattern recognition and classification technology can be used in this field, we can effectively improve the detection accuracy. This paper firstly introduce the basics knowledge of BP neural network, then use MATLAB neural network toolbox to build network models and used experimental data to train the net. The simulation results show the network´s performance is good.
  • Keywords
    backpropagation; chemical variables measurement; gas sensors; pattern classification; safety; sensor arrays; signal classification; BP neural network; MATLAB neural network toolbox; adaptive learning; catalytic combustion gas sensor array; chemical field; flammable gas detection; industrial field; intelligent classification strategy; network model; pattern classification; pattern recognition; poisonous gas detection; product-safety control; Artificial neural networks; Biological neural networks; Mathematical model; Neurons; Training; Transfer functions; Artificial Neural Networks Back Propagation Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Communications and Control (ICECC), 2011 International Conference on
  • Conference_Location
    Ningbo
  • Print_ISBN
    978-1-4577-0320-1
  • Type

    conf

  • DOI
    10.1109/ICECC.2011.6066460
  • Filename
    6066460