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Evaluation of model parameter accuracy by using joint confidence regions: application to low complexity neural networks to describe enzyme inactivation

Author

Listed:
  • Geeraerd, Annemie H.
  • Herremans, Carl H.
  • Ludikhuyze, Linda R.
  • Hendrickx, Marc E.
  • Van Impe, Jan F.

Abstract

An existing low complexity, black box artificial neural network model (ANN model) is investigated towards its more general applicability in the field of high isobaric–isothermal inactivation of enzymes. The use of this non-linear modeling technique makes it possible to describe accurately synergistic effects of pressure and temperature in contrast with more classical models used in this novel area of food processing.

Suggested Citation

  • Geeraerd, Annemie H. & Herremans, Carl H. & Ludikhuyze, Linda R. & Hendrickx, Marc E. & Van Impe, Jan F., 1998. "Evaluation of model parameter accuracy by using joint confidence regions: application to low complexity neural networks to describe enzyme inactivation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(1), pages 53-64.
    • Handle: RePEc:eee:matcom:v:48:y:1998:i:1:p:53-64
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