• DocumentCode
    2698984
  • Title

    Black Box Modeling of Steam Distillation Essential Oil Extraction System Using NNARX Structure

  • Author

    Rahiman, Mohd Hezri Fazalul ; Taib, Mohd Nasir ; Salleh, Yusof Md

  • Author_Institution
    Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
  • fYear
    2009
  • fDate
    1-3 April 2009
  • Firstpage
    324
  • Lastpage
    329
  • Abstract
    This paper evaluates the neural network autoregressive with exogenous (NNARX) structure in modeling the steam distillation essential oil extraction. The model order will be selected based on Rissanenpsilas minimum description length (MDL) information criterion. In the training of NNARX model, both unregularized and regularized models will be assessed. There are three regularization levels of the weight decay that will be implemented in this work. The number of hidden neuron and iteration will be optimized before the training session. The testing of the trained model will be based on R2, adjusted-R2, NMSE, RMSE, residual histogram and correlation tests. All results will be compared and evaluated with respect to the testing data.
  • Keywords
    autoregressive processes; chemical industry; distillation; essential oils; iterative methods; neural nets; production engineering computing; NNARX structure; Rissanenpsilas minimum description length; black box modeling; hidden neuron; information criterion; neural network autoregressive with exogenous structure; steam distillation essential oil extraction system; Calibration; Data acquisition; Data mining; Neural networks; Petroleum; Predictive models; Temperature control; Temperature measurement; Testing; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information and Database Systems, 2009. ACIIDS 2009. First Asian Conference on
  • Conference_Location
    Dong Hoi
  • Print_ISBN
    978-0-7695-3580-7
  • Type

    conf

  • DOI
    10.1109/ACIIDS.2009.95
  • Filename
    5176014