Anbieter: Second Story Books, ABAA, Rockville, MD, USA
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Hardcover. First Edition. Octavo, viii, 246 pages. In Very Good minus condition. Bound in red and purple paper with white and yellow lettering. Boards have minor shelf wear. Text block has minor cracking to gutter of title page. NOTE: Shelved in ND-E. 1377100. FP New Rockville Stock.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 114,44
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In den WarenkorbZustand: New. In.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 114,44
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 139,50
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In den WarenkorbZustand: New. pp. 258 Illus.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 152,09
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In den WarenkorbPaperback. Zustand: Brand New. 2010 edition. 256 pages. 9.20x6.10x0.61 inches. In Stock.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 153,36
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In den WarenkorbHardcover. Zustand: Brand New. 265 pages. 9.50x6.50x0.75 inches. In Stock.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Exploitation of Linkage Learning in Evolutionary Algorithms | Ying-Ping Chen | Taschenbuch | Adaptation, Learning, and Optimization | x | Englisch | 2012 | Springer | EAN 9783642263279 | 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 Berlin Heidelberg, 2012
ISBN 10: 3642263275 ISBN 13: 9783642263279
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.
Sprache: Englisch
Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2010
ISBN 10: 3642128335 ISBN 13: 9783642128332
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.