Stable mutations evolutionary algorithms von obuchowicz andrzej (7 Ergebnisse)

Sprache: Englisch
Verlag: Springer 2018
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Sprache: Englisch
Verlag: Springer 2019
Serie: Studies in Computational Intelligence, Buch 305 von 538. Buch 305 von 538 - Studies in Computational Intelligence
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Sprache: Englisch
Verlag: Springer-Verlag New York Inc 2019
Serie: Studies in Computational Intelligence, Buch 305 von 538. Buch 305 von 538 - Studies in Computational Intelligence
- Softcover
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Sprache: Englisch
Verlag: Springer 2018
Serie: Studies in Computational Intelligence, Buch 305 von 538. Buch 305 von 538 - Studies in Computational Intelligence
- Hardcover
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Sprache: Englisch
Verlag: Springer 2019
Serie: Studies in Computational Intelligence, Buch 305 von 538. Buch 305 von 538 - Studies in Computational Intelligence
- Softcover
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Taschenbuch. Zustand: Neu. Stable Mutations for Evolutionary Algorithms | Andrzej Obuchowicz | Taschenbuch | xiv | Englisch | 2019 | Springer | EAN 9783030131845 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Sprache: Englisch
Verlag: Springer International Publishing 2019
Serie: Studies in Computational Intelligence, Buch 305 von 538. Buch 305 von 538 - Studies in Computational Intelligence
- Softcover
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a set of theoretical and experimental results that describe the features of the wide family of -stable distributions (the normal distribution also belongs to this class) and their various applications in the mutation operator of ev…olutionary algorithms based on real-number representation of the individuals, and, above all, equip these algorithms with features that enrich their effectiveness in solving multi-modal, multi-dimensional global optimization problems. The overall conclusion of the research presented is that the appropriate choice of probabilistic model of the mutation operator for an optimization problem is crucial.Mutation is one of the most important operations in stochastic global optimization algorithms in the n-dimensional real space. It determines the method of search space exploration and exploitation. Most applications of these algorithms employ the normal mutation as a mutation operator. This choice is justified by the central limit theorem but is associated with a set of important limitations. Application of -stable distributions allows more flexible evolutionary models to be obtained than those with the normal distribution. The book presents theoretical analysis and simulation experiments, which were selected and constructed to expose the most important features of the examined mutation techniques based on -stable distributions. It allows readers to develop a deeper understanding of evolutionary processes with stable mutations and encourages them to apply these techniques to real-world engineering problems.

Sprache: Englisch
Verlag: Springer International Publishing 2018
Serie: Studies in Computational Intelligence, Buch 305 von 538. Buch 305 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 106,99
EUR 62,21 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a set of theoretical and experimental results that describe the features of the wide family of -stable distributions (the normal distribution also belongs to this class) and their various applications in the mutation operator of evolution…ary algorithms based on real-number representation of the individuals, and, above all, equip these algorithms with features that enrich their effectiveness in solving multi-modal, multi-dimensional global optimization problems. The overall conclusion of the research presented is that the appropriate choice of probabilistic model of the mutation operator for an optimization problem is crucial.Mutation is one of the most important operations in stochastic global optimization algorithms in the n-dimensional real space. It determines the method of search space exploration and exploitation. Most applications of these algorithms employ the normal mutation as a mutation operator. This choice is justified by the central limit theorem but is associated with a set of important limitations. Application of -stable distributions allows more flexible evolutionary models to be obtained than those with the normal distribution. The book presents theoretical analysis and simulation experiments, which were selected and constructed to expose the most important features of the examined mutation techniques based on -stable distributions. It allows readers to develop a deeper understanding of evolutionary processes with stable mutations and encourages them to apply these techniques to real-world engineering problems.