This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.
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This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering systems is inevitable. Representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums, are presented. "Evolutionary Computation in Dynamic and Uncertain Environments" is a valuable reference for scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, natural computing and evolutionary computation.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Bluesparrowhawk Books, Chestfield, KENT, Regno Unito
Hardcover. Condizione: New. No Jacket. Springer, 2007. Heavy hardback, no dustjacket. Unread copy. New & Sealed. book. Codice articolo HVY-17366
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Da: Basi6 International, Irving, TX, U.S.A.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Codice articolo ABEOCT25-241297
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Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Codice articolo ABBB-155672
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Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. State of the art of evolutionary algorithms in dynamic and uncertain environmentsState of the art of evolutionary algorithms in dynamic and uncertain environmentsIncludes supplementary material: sn.pub/extrasThis book compile. Codice articolo 4891383
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums. 632 pp. Englisch. Codice articolo 9783540497721
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Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9783540497721_new
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Da: preigu, Osnabrück, Germania
Buch. Condizione: Neu. Evolutionary Computation in Dynamic and Uncertain Environments | Shengxiang Yang (u. a.) | Buch | Studies in Computational Intelligence | xxiii | Englisch | 2007 | Springer | EAN 9783540497721 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 102118377
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Evolutionary computation is a class of problem optimization methodology with the inspiration from the natural evolution of species. In nature, the population of a species evolves by means of selection and variation. These two principles of natural evolution form the fundamental of evolutionary - gorithms (EAs). During the past several decades, EAs have been extensively studied by the computer science and arti cial intelligence communities. As a classofstochasticoptimizationtechniques,EAscanoftenoutperformclassical optimization techniques for di cult real world problems. Due to the ease of use and robustness, EAs have been applied to a wide variety of optimization problems. Most of these optimization problems ta- led are stationary and deterministic. However, many real-world optimization problems are subjected to dynamic and uncertain environments that are often impossible to avoid in practice. For example, the tness function is uncertain or noisy as a result of simulation errors, measurement errors or approximation errors. In addition, the design variables or environmental conditions may also perturb or change over time. For these dynamic and uncertain optimization problems, the objective of the EA is no longer to simply locate the global optimum solution, but to continuously track the optimum in dynamic en- ronments, or to nd a robust solution that operates optimally in the presence of uncertainties. This poses serious challenges to classical optimization te- niques and conventional EAs as well. However, conventional EAs with proper enhancements are still good tools of choice for optimization problems in - namic and uncertain environments.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 632 pp. Englisch. Codice articolo 9783540497721
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Da: AHA-BUCH GmbH, Einbeck, Germania
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Evolutionary computation is a class of problem optimization methodology with the inspiration from the natural evolution of species. In nature, the population of a species evolves by means of selection and variation. These two principles of natural evolution form the fundamental of evolutionary - gorithms (EAs). During the past several decades, EAs have been extensively studied by the computer science and arti cial intelligence communities. As a classofstochasticoptimizationtechniques,EAscanoftenoutperformclassical optimization techniques for di cult real world problems. Due to the ease of use and robustness, EAs have been applied to a wide variety of optimization problems. Most of these optimization problems ta- led are stationary and deterministic. However, many real-world optimization problems are subjected to dynamic and uncertain environments that are often impossible to avoid in practice. For example, the tness function is uncertain or noisy as a result of simulation errors, measurement errors or approximation errors. In addition, the design variables or environmental conditions may also perturb or change over time. For these dynamic and uncertain optimization problems, the objective of the EA is no longer to simply locate the global optimum solution, but to continuously track the optimum in dynamic en- ronments, or to nd a robust solution that operates optimally in the presence of uncertainties. This poses serious challenges to classical optimization te- niques and conventional EAs as well. However, conventional EAs with proper enhancements are still good tools of choice for optimization problems in - namic and uncertain environments. Codice articolo 9783540497721
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Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. 1st edition. 605 pages. 9.25x6.25x1.50 inches. In Stock. Codice articolo x-3540497722
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