BulDML at Institute of Mathematics and Informatics >
IMI Periodicals >
Serdica Journal of Computing >
2010 >
Volume 4 Number 1 >

Please use this identifier to cite or link to this item:

Title: Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms
Authors: Angelova, Maria
Tzonkov, Stoyan
Pencheva, Tania
Keywords: Genetic Algorithms
Parameter Identification
Fed-Batch Cultivation of S. Cerevisiae
Issue Date: 2010
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation: Serdica Journal of Computing, Vol. 4, No 1, (2010), 11p-18p
Abstract: Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.
ISSN: 1312-6555
Appears in Collections:Volume 4 Number 1

Files in This Item:

File Description SizeFormat
sjc111-vol4-num1-2010.pdf210.88 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0!   Creative Commons License