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Parameter Estimation of a Monod-Type Model Based on Genetic Algorithms and Sensitivity Analysis

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Large-Scale Scientific Computing (LSSC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4818))

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Abstract

Mathematical models and their parameters used to describe cell behavior constitute the key problem of bioprocess modelling, in practical, in parameter estimation. The model building leads to an information deficiency and to non unique parameter identification. While searching for new, more adequate modeling concepts, methods which draw their initial inspiration from nature have received the early attention. One of the most common direct methods for global search is genetic algorithm. A system of six ordinary differential equations is proposed to model the variables of the regarded cultivation process. Parameter estimation is carried out using real experimental data set from an E. coli MC4110 fed-batch cultivation process. In order to study and evaluate the links and magnitudes existing between the model parameters and variables sensitivity analysis is carried out. A procedure for consecutive estimation of four definite groups of model parameters based on sensitivity analysis is proposed. The application of that procedure and genetic algorithms leads to a successful parameter identification.

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Authors and Affiliations

  1. Centre of Biomedical Engineering Prof. Ivan Daskalov, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., 1113, Sofia, Bulgaria

    Olympia Roeva

Authors
  1. Olympia Roeva
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Editors and Affiliations

  1. Institute for Parallel Processing, Bulgarian Academy of Sciences, Acad. G. Bonchev, Bl. 25A, 1113, Sofia, Bulgaria

    Ivan Lirkov

  2. Institute for Parallel Processing, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 25-A, 1113, Sofia, Bulgaria

    Svetozar Margenov

  3. Department of Informatics and Mathematical Modelling, Technical University of Denmark, Richard Petersen Plads, Building 321, DK-2800, Kongens Lyngby, Denmark

    Jerzy Waśniewski

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Roeva, O. (2008). Parameter Estimation of a Monod-Type Model Based on Genetic Algorithms and Sensitivity Analysis. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2007. Lecture Notes in Computer Science, vol 4818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78827-0_69

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  • DOI: https://doi.org/10.1007/978-3-540-78827-0_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78825-6

  • Online ISBN: 978-3-540-78827-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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