Metaheuristics and Optimization in Computer and Electrical Engineering: Hybrid and Improved Algorithms (2) - Rilegato

 
9783031426841: Metaheuristics and Optimization in Computer and Electrical Engineering: Hybrid and Improved Algorithms (2)
Rilegato
ISBN 10: 3031426843 ISBN 13: 9783031426841
Casa editrice: Springer Nature, 2023

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer Nature
Data di pubblicazione
2023
Lingua
Inglese
ISBN 10 
3031426843
ISBN 13 
9783031426841
Rilegatura
Copertina rigida
Numero di pagine
500
Redattore
Razmjooy Navid, Ghadimi Noradin, Rajinikanth Venkatesan
Contatto del produttore
ProductSafety@springernature.com
ProductSafety@springernature.com

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Darmstadt
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Germania

Altre edizioni note dello stesso titolo

9783031426872: Metaheuristics and Optimization in Computer and Electrical Engineering: Volume 2: Hybrid and Improved Algorithms: 1077

Edizione in evidenza

ISBN 10:  3031426878 ISBN 13:  9783031426872
Casa editrice: Springer, 2024
Brossura