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Paired Structures, Imprecision Types and Two-Level Knowledge Representation by Means of Opposites Read chapter Read first chapter

2016 | OriginalPaper | Chapter

InterCriteria Analysis of Generation Gap Influence on Genetic Algorithms Performance

Authors : Olympia Roeva, Peter Vassilev

Published in: Novel Developments in Uncertainty Representation and Processing

Publisher: 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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Metadata
Title
InterCriteria Analysis of Generation Gap Influence on Genetic Algorithms Performance
Authors
Olympia Roeva
Peter Vassilev
Copyright Year
2016
Book
Novel Developments in Uncertainty Representation and Processing

Print ISBN: 978-3-319-26210-9

Electronic ISBN: 978-3-319-26211-6

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-26211-6_26

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