Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science: 975 (Studies in Computational Intelligence) - Softcover

Jin, Yaochu; Wang, Handing; Sun, Chaoli

Softcover

ISBN 10: 3030746429 ISBN 13: 9783030746421

Verlag: Springer, 2022

Inhaltsangabe

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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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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2022
• Sprache: Englisch
• ISBN 10: 3030746429
• ISBN 13: 9783030746421
• Einband: Tapa blanda
• Auflage: 1
• Anzahl der Seiten: 420
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Deutschland