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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.
| Autorius: | Ajith Abraham, Meera Ramadas, |
| Serija: | Intelligent Systems Reference Library |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2019 |
| Knygos puslapių skaičius: | 176 |
| ISBN-10: | 3030040968 |
| ISBN-13: | 9783030040963 |
| Formatas: | 241 x 160 x 16 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Metaheuristics for Data Clustering and Image Segmentation“
