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2016 | OriginalPaper | Buchkapitel

InterCriteria Analysis of Generation Gap Influence on Genetic Algorithms Performance

verfasst von : Olympia Roeva, Peter Vassilev

Erschienen in: Novel Developments in Uncertainty Representation and Processing

Verlag: Springer International Publishing

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Abstract

In this investigation InterCriteria Analysis (ICA) is applied to examine the influences of one of the genetic algorithms parameters—the generation gap (ggap). The investigation is carried out during the model parameter identification of E. coli MC4110 cultivation process. The apparatuses of index matrices and intuitionistic fuzzy sets, which are the core of ICA, are used to establish the relations between ggap and GAs outcomes (computational time and decision accuracy), on one hand, and cultivation process model parameters on the other hand. The obtained results after ICA application are analyzed in terms of convergence time and model accuracy and some conclusions about derived interactions are reported.

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Metadaten
Titel
InterCriteria Analysis of Generation Gap Influence on Genetic Algorithms Performance
verfasst von
Olympia Roeva
Peter Vassilev
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-26211-6_26