Metaheuristics for Data Clustering and Image Segmentation (Intelligent Systems Reference Library, 152)
Language: English
Published by Springer, 2019
Series: Book 123 of 188 - Intelligent Systems Reference Library
- Hardcover
- New
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
AbeBooks seller since March 25, 2015
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Seller Inventory # ria9783030040963_new
- Title
- Metaheuristics for Data Clustering and Image Segmentation (Intelligent Systems Reference Library, 152)
- Author
- Ramadas, Meera; Abraham, Ajith
- Publisher
- Springer
- Publication year
- 2019
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3030040968
- ISBN 13
- 9783030040963
- Item weight
- 547 grams
- Series
- Book 123 of 188: Intelligent Systems Reference Library
In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
"Synopsis" may belong to another edition of this title.
From the Back Cover
In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
"About the title" may belong to another edition of this title.
Ria Christie Collections
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