Title: Evaluation of model parameter accuracy by using joint confidence regions: application to low complexity neural networks to describe enzyme inactivation
Authors: Geeraerd, Annemie ×
Herremans, CH
Ludikhuyze, LR
Hendrickx, Marc
Van Impe, Jan #
Issue Date: 1998
Series Title: Mathematics and computers in simulation vol:48 issue:1 pages:53-64
Conference: date:Katholieke Univ Leuven, Fac Agr & Appl Biol Sci, Dept Food & Microbial Technol, B-3001 Heverlee, Belgium
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. The modeling approach will be illustrated on a new experimental data set, being used to validate the structural characteristics of the selected ANN model. Moreover, joint confidence regions, taking into account the correlation between model parameters, will be constructed. The results will be translated towards the raw experimental data. (C) 1998 IMACS/Elsevier Science B.V.
ISSN: 0378-4754
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Mechatronics, Biostatistics and Sensors (MeBioS)
Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
× corresponding author
# (joint) last author

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