Condizione: 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. Codice articolo 608128468

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Data-Driven Evolutionary Optimization

Yaochu Jin

Editore: Springer International Publishing, Springer Nature Switzerland Jun 2022, 2022

ISBN 10: 3030746429 ISBN 13: 9783030746421

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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania

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Taschenbuch. Condizione: 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. Codice articolo 9783030746421

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Data-Driven Evolutionary Optimization : Integrating Evolutionary Computation, Machine Learning and Data Science

Yaochu Jin

Editore: Springer International Publishing, Springer Nature Switzerland, 2022

ISBN 10: 3030746429 ISBN 13: 9783030746421

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Da: AHA-BUCH GmbH, Einbeck, Germania

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Taschenbuch. Condizione: 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. Codice articolo 9783030746421

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