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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| Main Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boca Raton
CRC Press, Taylor & Francis Group
2024
|
| Edition: | First edition |
| Subjects: | |
| Online Access: | DE-824 Volltext |
| Summary: | 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 |
| Item Description: | OCLC-licensed vendor bibliographic record |
| Physical Description: | 1 Online-Ressource (xviii, 452 Seiten) |
| ISBN: | 9781003422426 100342242X 9781040000366 1040000363 9781040000342 1040000347 |
| DOI: | 10.1201/9781003422426 |
Staff View
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| 520 | |a 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 | ||
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| illustrated | Not Illustrated |
| indexdate | 2025-05-23T16:05:24Z |
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| isbn | 9781003422426 100342242X 9781040000366 1040000363 9781040000342 1040000347 |
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| spelling | Wang, Gai-Ge 1984- Verfasser aut Metaheuristic Algorithms Theory and Practice Gai-Ge Wang, Xiaoqi Zhao, and Keqin Li First edition Boca Raton CRC Press, Taylor & Francis Group 2024 1 Online-Ressource (xviii, 452 Seiten) txt rdacontent c rdamedia cr rdacarrier OCLC-licensed vendor bibliographic record 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 COMPUTERS / General bisacsh COMPUTERS / Programming / Algorithms bisacsh COMPUTERS / Artificial Intelligence bisacsh Heuristic algorithms Zhao, Xiaoqi aut Li, Keqin 1963- aut Erscheint auch als Druck-Ausgabe 1032714042 Erscheint auch als Druck-Ausgabe 9781032714042 Erscheint auch als Druck-Ausgabe 9781032727608 https://doi.org/10.1201/9781003422426 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Wang, Gai-Ge 1984- Zhao, Xiaoqi Li, Keqin 1963- Metaheuristic Algorithms Theory and Practice COMPUTERS / General bisacsh COMPUTERS / Programming / Algorithms bisacsh COMPUTERS / Artificial Intelligence bisacsh Heuristic algorithms |
| title | Metaheuristic Algorithms Theory and Practice |
| title_auth | Metaheuristic Algorithms Theory and Practice |
| title_exact_search | Metaheuristic Algorithms Theory and Practice |
| title_full | Metaheuristic Algorithms Theory and Practice Gai-Ge Wang, Xiaoqi Zhao, and Keqin Li |
| title_fullStr | Metaheuristic Algorithms Theory and Practice Gai-Ge Wang, Xiaoqi Zhao, and Keqin Li |
| title_full_unstemmed | Metaheuristic Algorithms Theory and Practice Gai-Ge Wang, Xiaoqi Zhao, and Keqin Li |
| title_short | Metaheuristic Algorithms |
| title_sort | metaheuristic algorithms theory and practice |
| title_sub | Theory and Practice |
| topic | COMPUTERS / General bisacsh COMPUTERS / Programming / Algorithms bisacsh COMPUTERS / Artificial Intelligence bisacsh Heuristic algorithms |
| topic_facet | COMPUTERS / General COMPUTERS / Programming / Algorithms COMPUTERS / Artificial Intelligence Heuristic algorithms |
| url | https://doi.org/10.1201/9781003422426 |
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