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Integrating Meta-heuristics and Machine Learning for Real-world Optimization Problems

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Classement des ventes 110783dans
CHF165.50

Description

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.

Détails

Autres ISBN/GTIN9783030990794
Type de produitE-book
ReliureE-book
FormatPDF
Indications sur le formatfiligrane
Date de parution04.06.2022
Edition1st ed. 2022
No. de série1038
Pages497 pages
LangueAnglais
IllustrationsIX, 497 p. 227 illus., 183 illus. in color.
N° article40383771
CataloguesVC
Source des données n°3700783
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Série

Auteur

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