Metaheuristics and Optimization in Computer and Electrical Engineering

Lieferzeit: Lieferbar innerhalb 14 Tagen

171,19 

Volume 2: Hybrid and Improved Algorithms, Lecture Notes in Electrical Engineering 1077

ISBN: 3031426843
ISBN 13: 9783031426841
Herausgeber: Navid Razmjooy/Noradin Ghadimi/Venkatesan Rajinikanth
Verlag: Springer Verlag GmbH
Umfang: viii, 491 S., 44 s/w Illustr., 181 farbige Illustr., 491 p. 225 illus., 181 illus. in color.
Erscheinungsdatum: 08.10.2023
Auflage: 1/2023
Produktform: Gebunden/Hardback
Einband: Gebunden

Presents a review of selected hybrid and improved meta-heuristic methods and their applicationsExplores the possibility of using different kinds of optimization algorithmsProvides with different case studies in computer and electrical engineering

Artikelnummer: 282912 Kategorie:

Beschreibung

This book discusses different methods of modifying the original metaheuristics and their application in computer and electrical engineering. As the race to develop advanced technology accelerates, a new era of "metaheuristics" has emerged. Through researched-based techniques and collaborative problem-solving, this book helps engineers to find efficient solutions to their engineering challenges. With the help of an expert guide and the collective knowledge of the engineering community, this comprehensive guide shows readers how to use machine learning and other AI techniques to reinvent smart engineering. From understanding the fundamentals to mastering the latest metaheuristics models, this guide provides with the skills and knowledge that need to stay ahead in the technology race. In the previous volume, authors focused on the application of original metaheuristics on electrical and computer sciences. This volume learns how AI and modified metaheuristics can be used to optimize algorithms and create more efficient electrical engineering designs. It gets insights on how data can be effectively processed and discover new techniques for creating sophisticated automation systems. It maximizes the potential of readers computer and electrical engineering projects with powerful metaheuristics and optimization techniques.

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