• DocumentCode
    571591
  • Title

    Application of Neural Network in the Analysis of Near-Infrared Spectra

  • Author

    Zuo, Ping ; Pang, Shichun ; Feng, Xue ; Gao, Yanchao ; Qin, Dandan

  • Author_Institution
    Foundational Dept. of Aviation, Univ. of Air Force, Changchun, China
  • Volume
    1
  • fYear
    2012
  • fDate
    26-27 Aug. 2012
  • Firstpage
    155
  • Lastpage
    158
  • Abstract
    The main problem in the spectrum analysis technology is the difficulty in locating the target which will affect the predication and the analysis. How to choose the right mathematic model becomes the key point in the spectrum analysis. This paper designs the practical manual neural network model to locate the target and predicate. This paper uses error backward direction propagation calculation method and establishes three-layer neural network to solve the problems such as the spectrum peaks overlap seriously and noise is big in the spectrum analysis. When the quantity of samples to be located the target is significant, employ manual neural network method to analyze and discuss the corn´s protein content and near-infrared spectrum. By analyzing the experimental result this paper concludes that manual neural network method performs better than linear regression method and partial least-squares method and obtains ideal result.
  • Keywords
    backpropagation; food products; neural nets; production engineering computing; proteins; spectrochemical analysis; corn protein content; error backward direction propagation calculation method; mathematic model; near infrared spectra analysis; neural network model; target location; Absorption; Chemicals; Linear regression; Manuals; Mathematical model; Neural networks; Spectral analysis; location and predication; manual neural network method; spectrum analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
  • Conference_Location
    Nanchang, Jiangxi
  • Print_ISBN
    978-1-4673-1902-7
  • Type

    conf

  • DOI
    10.1109/IHMSC.2012.45
  • Filename
    6305649