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Añadir al carritoTaschenbuch. Condición: Neu. Data-Driven Evolutionary Optimization | Integrating Evolutionary Computation, Machine Learning and Data Science | Yaochu Jin (u. a.) | Taschenbuch | xxv | Englisch | 2022 | Springer | EAN 9783030746421 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Idioma: Inglés
Publicado por Springer International Publishing, Springer Nature Switzerland, 2022
ISBN 10: 3030746429 ISBN 13: 9783030746421
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.
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Idioma: Inglés
Publicado por Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030746429 ISBN 13: 9783030746421
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applic.
Idioma: Inglés
Publicado por Springer International Publishing, Springer Nature Switzerland Jun 2022, 2022
ISBN 10: 3030746429 ISBN 13: 9783030746421
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included. 420 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Jun 2022, 2022
ISBN 10: 3030746429 ISBN 13: 9783030746421
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 181,89
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available.This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 420 pp. Englisch.
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