Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
Language: English
Published by Springer Nature Switzerland AG, CH, 2026
Series: Book 526 of 538 - Studies in Computational Intelligence
- Softcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
£ 156.43
Quantity: Over 20 available
Add to basketItem description from seller
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.…
Seller Inventory # LU-9783030990817
- Title
- Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
- Author
- Mohamed Abd Elaziz, Diego Oliva, Essam Halim Houssein, Laith Abualigah
- Publisher
- Springer Nature Switzerland AG, CH
- Publication year
- 2026
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 3030990818
- ISBN 13
- 9783030990817
- Edition
- 2022 ed.
- Item weight
- 712 grams
- Dimensions
- 15.49 x 2.62 x 23.5 cm
- Series
- Book 526 of 538: Studies in Computational Intelligence
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.
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London, London, United Kingdom
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