• DocumentCode
    134536
  • Title

    Application of ANN in agarwood oil grade classification

  • Author

    Ismail, Nur ; Rahiman, M.H.F. ; Taib, M.N. ; Ali, N.A.M. ; Jamil, M. ; Tajuddin, S.N.

  • Author_Institution
    Fac. of Electr. Eng., UiTM Shah Alam, Shah Alam, Malaysia
  • fYear
    2014
  • fDate
    7-9 March 2014
  • Firstpage
    216
  • Lastpage
    220
  • Abstract
    This paper presents the application of Artificial Neural Network (ANN) in agarwood oil grade classification. The work involved of the extraction of chemical compounds by GC-MS, identification the significant chemical compounds using Z-score, generating the synthetic data using a dedicated formulae and application of ANN classification. The ANN classification is performed and its performance is measured using accuracy, sensitivity and specificity. The result showed that the performance of ANN classification for original GC-MS data is increasing when the data is added with synthetic data. This study showed that the ANN application in this study required a large number of sample size for it to have high accuracy in classification.
  • Keywords
    chemical engineering computing; chemical technology; chromatography; essential oils; mass spectra; neural nets; production engineering computing; quality control; ANN classification; GC-MS; Z-score; agarwood oil grade classification; artificial neural network; chemical compounds; extraction; Accuracy; Artificial neural networks; Chemical compounds; Market research; Oils; Signal processing; Training; ANN; agarwood oil; chemical compounds; classification; grade;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing & its Applications (CSPA), 2014 IEEE 10th International Colloquium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4799-3090-6
  • Type

    conf

  • DOI
    10.1109/CSPA.2014.6805751
  • Filename
    6805751