Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems: 1038 (Studies in Computational Intelligence) - Tapa dura
Sinopsis
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.
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De la contraportada
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.
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems (Studies in Computational Intelligence, 1038)
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 512 pp. Englisch. Nº de ref. del artículo: 9783030990787
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Integrating Meta-heuristics and Machine Learning for Real-world Optimization Problems
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Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030990788
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 . Nº de ref. del artículo: 566539853
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems (Studies in Computational Intelligence, 1038)
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Buch. Condición: Neu. Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems | Essam Halim Houssein (u. a.) | Buch | ix | Englisch | 2022 | Springer | EAN 9783030990787 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 121257822
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
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Springer International Publishing, Springer Nature Switzerland Jun 2022, 2022
ISBN 10: 3030990788
ISBN 13: 9783030990787
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Buch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 512 pp. Englisch. Nº de ref. del artículo: 9783030990787
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
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Springer International Publishing, 2022
ISBN 10: 3030990788
ISBN 13: 9783030990787
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783030990787
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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems (Studies in Computational Intelligence, 1038)
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