Metaheuristics for Data Clustering and Image Segmentation / by Meera Ramadas, Ajith Abraham.
By: Ramadas, Meera, autor
Contributor(s): SpringerLink (Online service)
| Abraham, Ajith, autor
Series: (Intelligent Systems Reference Library, 1868-4394; 152); (Intelligent Technologies and Robotics (Springer-42732)).Publisher: Cham : Imprint: Springer, 2019Description: 1 recurso en línea (IX, 163 páginas).ISBN: 9783030040970.Subject: Algoritmos computacionales
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.9.A43 2019 EB (Browse shelf(Opens below)) | Acceso electrónico | eBooks26062278 |
Browsing Madrid Digital shelves, Shelving location: Acceso Electrónico (UEM) Close shelf browser (Hides shelf browser)
| QA76.9 .A43 2018 EB Algorithms and Applications : ALAP 2018 | QA76.9.A43 2018 EB Advances in Metaheuristics Algorithms: Methods and Applications | QA76.9 .A43 2019 EB Harmony Search and Nature Inspired Optimization Algorithms : Theory and Applications, ICHSA 2018 | QA76.9.A43 2019 EB Metaheuristics for Data Clustering and Image Segmentation | QA76.9 .A43 2020 EB Recent metaheuristics algorithms for parameter identification | QA76.9. A43 2020 EB Advances in harmony search, soft computing and applications | QA76.9.A43 2021 EB Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms |
Introduction -- METAHEURISTICS AND DATA CLUSTERING -- REVISED MUTATION STRATEGY FOR DIFFERENTIAL EVOLUTION ALGORITHM -- SEARCH strategy Flower Pollination Algorithm with Differential Evolution. .
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.
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