Téléchargez le livre : Evolutionary Data Clustering: Algorithms and Applications

Evolutionary Data Clustering: Algorithms and Applications

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Éditeur :

Springer


Collection :

Algorithms for Intelligent Systems

Paru le : 2021-02-20

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Description
This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering indiverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.
Pages
248 pages
Collection
Algorithms for Intelligent Systems
Parution
2021-02-20
Marque
Springer
EAN papier
9789813341906
EAN PDF
9789813341913
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
24
Taille du fichier
6666 Ko
Prix
179,34 €
EAN EPUB
9789813341913
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
24
Taille du fichier
13179 Ko
Prix
179,34 €

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