Evolutionary Data Clustering Algorithms and Applications is popular PDF and ePub book, written by Ibrahim Aljarah in 2021-02-20, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Evolutionary Data Clustering Algorithms and Applications can be Read Online from any device for your convenience.
Evolutionary Data Clustering Algorithms and Applications Book PDF Summary
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.
Detail Book of Evolutionary Data Clustering Algorithms and Applications PDF
- Author : Ibrahim Aljarah
- Release : 20 February 2021
- Publisher : Springer Nature
- ISBN : 9789813341913
- Genre : Technology & Engineering
- Total Page : 248 pages
- Language : English
- PDF File Size : 18,8 Mb
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