Metaheuristics and optimization in computer and electrical engineering. Volume 2, Hybrid and improved algorithms / Navid Razmjooy, Noradin Ghadimi, Venkatesan Rajinikanth, editors.

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 collaborat...

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Bibliographic Details
Other Authors: Razmjooy, Navid, 1987- (Editor), Ghadimi, Noradin (Editor), Rajinikanth, Venkatesan (Editor)
Format: eBook
Language:English
Published: Cham : Springer, [2023]
Series:Lecture notes in electrical engineering ; v. 1077.
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Online Access:Click for online access
Description
Summary: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.
Physical Description:1 online resource (viii, 491 pages) : illustrations (chiefly color).
ISBN:9783031426858
3031426851
ISSN:1876-1119 ;
Source of Description, Etc. Note:Online resource; title from PDF title page (SpringerLink, viewed October 13, 2023).