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Verlag: Engineering Science Reference, 2018
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Verlag: Engineering Science Reference 2018-09-14, 2018
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Verlag: Engineering Science Reference, 2018
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In den WarenkorbZustand: New. Genetic algorithms (GA) and evolution strategies (ES) are relatively new stochastic based techniques for solving engineering problems on computers. GA and ES are based on a loose biological analogy: evolutionary theory (mutation, crossover, selection, survival of the fittest). Editor(s): Miettinen, K.; Neittaanmaki, Pekka; Makela, M. M.; Periaux, Jacques. Num Pages: 500 pages, references. BIC Classification: PBWH; TBJ; TGB; UYAM; UYQ. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 254 x 175 x 32. Weight in Grams: 1010. . 1999. 1st Edition. Hardcover. . . . .
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In den WarenkorbZustand: New. Genetic algorithms (GA) and evolution strategies (ES) are relatively new stochastic based techniques for solving engineering problems on computers. GA and ES are based on a loose biological analogy: evolutionary theory (mutation, crossover, selection, survival of the fittest). Editor(s): Miettinen, K.; Neittaanmaki, Pekka; Makela, M. M.; Periaux, Jacques. Num Pages: 500 pages, references. BIC Classification: PBWH; TBJ; TGB; UYAM; UYQ. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 254 x 175 x 32. Weight in Grams: 1010. . 1999. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
Buch. Zustand: Neu. Neuware - Evolutionäre Algorithmen sind Methoden künstlicher Intelligenz, die die Natur imitieren und für ihre Robustheit bei der Durchsuchung großer Räume und bei der Auffindung von Optima nahe des globalen Optimums bekannt sind. Dieser Band enthält die Vortragsmanuskripte des dritten EUROGEN-Kurses (Jyväskylä, Finnland, Mai/Juni 1999), in dessen Mittelpunkt die Anwendung des evolutionären Computings auf reale Probleme der Ingenieurtechnik steht. (05/99).
Sprache: Englisch
Verlag: John Wiley & Sons Inc, New York, 1999
ISBN 10: 0471999024 ISBN 13: 9780471999027
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Hardcover. Zustand: new. Hardcover. Evolutionary Algorithms in Engineering and Computer Science Edited by K. Miettinen, University of Jyvaeskylae, Finland M. M. Maekelae, University of Jyvaeskylae, Finland P. Neittaanmaeki, University of Jyvaeskylae, Finland J. Periaux, Dassault Aviation, France What is Evolutionary Computing? Based on the genetic message encoded in DNA, and digitalized algorithms inspired by the Darwinian framework of evolution by natural selection, Evolutionary Computing is one of the most important information technologies of our times. Evolutionary algorithms encompass all adaptive and computational models of natural evolutionary systems - genetic algorithms, evolution strategies, evolutionary programming and genetic programming. In addition, they work well in the search for global solutions to optimization problems, allowing the production of optimization software that is robust and easy to implement. Furthermore, these algorithms can easily be hybridized with traditional optimization techniques. This book presents state-of-the-art lectures delivered by international academic and industrial experts in the field of evolutionary computing. It bridges artificial intelligence and scientific computing with a particular emphasis on real-life problems encountered in application-oriented sectors, such as aerospace, electronics, telecommunications, energy and economics. This rapidly growing field, with its deep understanding and assesssment of complex problems in current practice, provides an effective, modern engineering tool. This book will therefore be of significant interest and value to all postgraduates, research scientists and practitioners facing complex optimization problems. Genetic algorithms (GA) and evolution strategies (ES) are relatively new stochastic based techniques for solving engineering problems on computers. GA and ES are based on a loose biological analogy: evolutionary theory (mutation, crossover, selection, survival of the fittest). This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Sprache: Englisch
Verlag: John Wiley & Sons Inc, New York, 1999
ISBN 10: 0471999024 ISBN 13: 9780471999027
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In den WarenkorbHardcover. Zustand: new. Hardcover. Evolutionary Algorithms in Engineering and Computer Science Edited by K. Miettinen, University of Jyvaeskylae, Finland M. M. Maekelae, University of Jyvaeskylae, Finland P. Neittaanmaeki, University of Jyvaeskylae, Finland J. Periaux, Dassault Aviation, France What is Evolutionary Computing? Based on the genetic message encoded in DNA, and digitalized algorithms inspired by the Darwinian framework of evolution by natural selection, Evolutionary Computing is one of the most important information technologies of our times. Evolutionary algorithms encompass all adaptive and computational models of natural evolutionary systems - genetic algorithms, evolution strategies, evolutionary programming and genetic programming. In addition, they work well in the search for global solutions to optimization problems, allowing the production of optimization software that is robust and easy to implement. Furthermore, these algorithms can easily be hybridized with traditional optimization techniques. This book presents state-of-the-art lectures delivered by international academic and industrial experts in the field of evolutionary computing. It bridges artificial intelligence and scientific computing with a particular emphasis on real-life problems encountered in application-oriented sectors, such as aerospace, electronics, telecommunications, energy and economics. This rapidly growing field, with its deep understanding and assesssment of complex problems in current practice, provides an effective, modern engineering tool. This book will therefore be of significant interest and value to all postgraduates, research scientists and practitioners facing complex optimization problems. Genetic algorithms (GA) and evolution strategies (ES) are relatively new stochastic based techniques for solving engineering problems on computers. GA and ES are based on a loose biological analogy: evolutionary theory (mutation, crossover, selection, survival of the fittest). This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 500 pages. 10.25x6.75x1.25 inches. In Stock. This item is printed on demand.