Metaheuristic Algorithms: Theory and Practice

This book introduces the theory and applications of metaheuristic algorithms. It also provides methods for solving practical problems in such fields as software engineering, image recognition, video networks, and in the oceans. In the theoretical section, the book introduces the information feedback...

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Bibliographische Detailangaben
Hauptverfasser: Wang, Gai-Ge 1984- (VerfasserIn), Zhao, Xiaoqi (VerfasserIn), Li, Keqin 1963- (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Boca Raton CRC Press, Taylor & Francis Group 2024
Ausgabe:First edition
Schlagworte:
Online-Zugang:DE-824
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Zusammenfassung:This book introduces the theory and applications of metaheuristic algorithms. It also provides methods for solving practical problems in such fields as software engineering, image recognition, video networks, and in the oceans. In the theoretical section, the book introduces the information feedback model, learning-based intelligent optimization, dynamic multi-objective optimization, and multi-model optimization. In the applications section, the book presents applications of optimization algorithms to neural architecture search, fuzz testing, oceans, and image processing. The neural architecture search chapter introduces the latest NAS method. The fuzz testing chapter uses multi-objective optimization and ant colony optimization to solve the seed selection and energy allocation problems in fuzz testing. In the ocean chapter, deep learning methods such as CNN, transformer, and attention-based methods are used to describe ENSO prediction and image processing for marine fish identification, and to provide an overview of traditional classification methods and deep learning methods. Rich in examples, this book will be a great resource for students, scholars, and those interested in metaheuristic algorithms, as well as professional practitioners and researchers working on related topics
Beschreibung:OCLC-licensed vendor bibliographic record
Beschreibung:1 Online-Ressource (xviii, 452 Seiten)
ISBN:9781003422426
100342242X
9781040000366
1040000363
9781040000342
1040000347
DOI:10.1201/9781003422426

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