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[null,"1.","Record Nr.",null,"UNINA9910483304803321"]
[null,null,"Titolo",null,"Evolutionary Data Clustering: Algorithms and Applications / / edited by Ibrahim Aljarah, Hossam Faris, Seyedali Mirjalili"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021"]
[null,null,"ISBN",null,"981-334-191-2"]
[null,null,"Edizione",null,"[1st ed. 2021.]"]
[null,null,"Descrizione fisica",null,"1 online resource (253 pages) : illustrations"]
[null,null,"Collana",null,"Algorithms for Intelligent Systems, , 2524-7573"]
[null,null,"Disciplina",null,"518.1"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Mathematical optimization"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Optimization"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Introduction to Evolutionary Data Clustering and its Applications -- A Comprehensive Review of Evaluation and Fitness Measures for Evolutionary Data Clustering -- A Grey Wolf based Clustering Algorithm for Medical Diagnosis Problems -- EEG-based Person Identification Using Multi-Verse Optimizer As Unsupervised Clustering Techniques -- Review of Evolutionary Data Clustering Algorithms for Image Segmentation -- Classification Approach based on Evolutionary Clustering and its Application for Ransomware Detection."]
[null,null,null,"Sommario/riassunto","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 "]
[{"$nulls":4},"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."]