InterCriteria Analysis Approach to Parameter Identification of a Fermentation Process Model

  • Tania Pencheva
  • Maria Angelova
  • Peter Vassilev
  • Olympia Roeva
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 401)

Abstract

In this investigation recently developed InterCriteria Analysis (ICA) is applied aiming at examination of the influence of a genetic algorithm (GA) parameter in the procedure of a parameter identification of a fermentation process model. Proven as the most sensitive GA parameter, generation gap is in the focus of this investigation. The apparatuses of index matrices and intuitionistic fuzzy sets, laid in the ICA core, are implemented to establish the relations between investigated here generation gap, from one side, and model parameters of fed-batch fermentation process of Saccharomyces cerevisiae, from the other side. The obtained results after ICA application are analysed towards convergence time and model accuracy and some conclusions about observed interactions are derived.

Keywords

InterCriteria analysis Genetic algorithms Generation gap Parameter identification S. cerevisiae 

Notes

Acknowledgments

The work is supported by the Bulgarian National Scientific Fund under the grant DFNI-I-02-5 “InterCriteria Analysis—A New Approach to Decision Making”.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Tania Pencheva
    • 1
  • Maria Angelova
    • 1
  • Peter Vassilev
    • 1
  • Olympia Roeva
    • 1
  1. 1.Institute of Biophysics and Biomedical EngineeringBulgarian Academy of SciencesSofiaBulgaria

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