Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems

Lieferzeit: Lieferbar innerhalb 14 Tagen

149,79 

Studies in Computational Intelligence 1038

ISBN: 3030990818
ISBN 13: 9783030990817
Herausgeber: Essam Halim Houssein/Mohamed Abd Elaziz/Diego Oliva et al
Verlag: Springer Verlag GmbH
Umfang: ix, 497 S., 44 s/w Illustr., 183 farbige Illustr., 497 p. 227 illus., 183 illus. in color.
Erscheinungsdatum: 12.03.2026
Auflage: 1/2026
Produktform: Kartoniert
Einband: Kartoniert

This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.

Artikelnummer: 9405009 Kategorie:

Beschreibung

This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material canbe helpful for research from the evolutionary computation, artificial intelligence communities.  

Herstellerkennzeichnung:


Springer Verlag GmbH
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69121 Heidelberg
DE

E-Mail: juergen.hartmann@springer.com

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