evolutionary data clustering algorithms (20 résultats)

Etat : New. In.

Etat : New. In.

Taschenbuch. Etat : Neu. Evolutionary Data Clustering: Algorithms and Applications | Ibrahim Aljarah (u. a.) | Taschenbuch | Algorithms for Intelligent Systems | xii | Englisch | 2022 | Springer | EAN 9789813341937 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Etat : New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Etat : New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Hardcover. Etat : Brand New. 260 pages. 9.25x6.10x9.21 inches. In Stock.

Etat : new. Questo è un articolo print on demand.

Etat : new. Questo è un articolo print on demand.

Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an in-depth analysis of the current evolutionary clustering techniquesFeatures a range of proven and recent nature-inspired algorithms used to data clusteringServes as a reference resource for researchers and academicians.

Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an in-depth analysis of the current evolutionary clustering techniquesFeatures a range of proven and recent nature-inspired algorithms used to data clusteringServes as a reference resource for researchers and academicians.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 260 pp. Englisch.

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 260 pp. Englisch.

Etat : New. Print on Demand.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.

Etat : New. Print on Demand.

Etat : New. PRINT ON DEMAND.

Etat : New. PRINT ON DEMAND.