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中图分类法:
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TP18 版次： |
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题名:
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Evolutionary data clustering : [ algorithms and applications /] / , |
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出版发行:
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出版地： Singapore : 出版社： Springer, 出版日期： [2021] |
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载体形态:
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xii, 248 pages : illustrations (chiefly color) ; 25 cm. |
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内容提要:
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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. |
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主题词:
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Computational intelligence. |
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主题词:
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Evolutionary computation. |
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主题词:
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Cluster analysis. |
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主题词:
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Algorithms. |
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主题词:
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Data mining. |
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主题词:
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Mathematical optimization. |
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主要责任者:
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Aljarah, Ibrahim, Aljarah, Ibrahim, |
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主要责任者:
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Faris, Hossam, Faris, Hossam, |
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主要责任者:
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Mirjalili, Seyedali, Mirjalili, Seyedali, |