03647nam 22006615 450 991048330480332120251113193624.0981-334-191-210.1007/978-981-33-4191-3(CKB)4100000011773947(MiAaPQ)EBC6485334(PPN)253856914(Au-PeEL)EBL6485334(OCoLC)1243554687(DE-He213)978-981-33-4191-3(EXLCZ)99410000001177394720210220d2021 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierEvolutionary Data Clustering: Algorithms and Applications /edited by Ibrahim Aljarah, Hossam Faris, Seyedali Mirjalili1st ed. 2021.Singapore :Springer Nature Singapore :Imprint: Springer,2021.1 online resource (253 pages) illustrationsAlgorithms for Intelligent Systems,2524-7573981-334-190-4 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.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.Algorithms for Intelligent Systems,2524-7573Computational intelligenceAlgorithmsData miningMathematical optimizationComputational IntelligenceAlgorithmsData Mining and Knowledge DiscoveryOptimizationComputational intelligence.Algorithms.Data mining.Mathematical optimization.Computational Intelligence.Algorithms.Data Mining and Knowledge Discovery.Optimization.518.1Faris HossamMirjalili SeyedaliAljarah IbrahimMiAaPQMiAaPQMiAaPQBOOK9910483304803321Evolutionary data clustering2853198UNINA