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2016 | OriginalPaper | Buchkapitel

InterCriteria Analysis Approach to Parameter Identification of a Fermentation Process Model

verfasst von : Tania Pencheva, Maria Angelova, Peter Vassilev, Olympia Roeva

Erschienen in: Novel Developments in Uncertainty Representation and Processing

Verlag: Springer International Publishing

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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.

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Metadaten
Titel
InterCriteria Analysis Approach to Parameter Identification of a Fermentation Process Model
verfasst von
Tania Pencheva
Maria Angelova
Peter Vassilev
Olympia Roeva
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-26211-6_33