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Erschienen in:
Intercriteria Analysis and Arithmetic Functions Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

On Different Algorithms for InterCriteria Relations Calculation

verfasst von : Olympia Roeva, Peter Vassilev, Nikolay Ikonomov, Maria Angelova, Jun Su, Tania Pencheva

Erschienen in: Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications

Verlag: Springer International Publishing

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Abstract

Contemporary InterCriteria analysis (ICrA) approach for searching of existing or unknown correlations between multiple objects against multiple criteria is applied here. Altogether five different algorithms for InterCriteria relations calculation have been examined to render the influence of the genetic algorithm parameters on the algorithm performance. Two cases, i.e. the model parameter identification of E. coli and S. cerevisiae fed-batch fermentation processes, are considered. In this investigation \(\mu \)-biased, Balanced, \(\nu \)-biased, Unbiased, as well as the newly elaborated and proposed here Weighted algorithm have been consequently applied and thoroughly examined. The obtained results for considered here two Case studies have been compared showing that the most reliable algorithm is the \(\mu \)-biased one.

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Vorheriges Kapitel Image to Sound Encryption Using a Self-organizing Map Neural Network
Nächstes Kapitel Defining Consonance Thresholds in InterCriteria Analysis: An Overview
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Metadaten
Titel
On Different Algorithms for InterCriteria Relations Calculation
verfasst von
Olympia Roeva
Peter Vassilev
Nikolay Ikonomov
Maria Angelova
Jun Su
Tania Pencheva
Copyright-Jahr
2019
Buch
Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications

Print ISBN: 978-3-319-78930-9

Electronic ISBN: 978-3-319-78931-6

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-78931-6_10