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Anglický jazyk
Evolutionary Data Clustering: Algorithms and Applications
Autor: Ibrahim Aljarah
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... Viac o knihe
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178.19 €
bežná cena: 197.99 €
O knihe
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 in diverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.
- Vydavateľstvo: Springer Nature Singapore
- Rok vydania: 2021
- Formát: Hardback
- Rozmer: 241 x 160 mm
- Jazyk: Anglický jazyk
- ISBN: 9789813341906
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