A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications

被引：109

作者：

Abualigah, Laith ^{[1
]}

Diabat, Ali ^{[2
,3
]}

Geem, Zong Woo ^{[4
]}

机构：

[1] Amman Arab Univ, Fac Comp Sci & Informat, Amman 11953, Jordan

[2] New York Univ Abu Dhabi, Div Engn, Abu Dhabi 129188, U Arab Emirates

[3] NYU, Tandon Sch Engn, Dept Civil & Urban Engn, Brooklyn, NY 11201 USA

[4] Gachon Univ, Dept Energy IT, Seongnam 13120, South Korea

来源：

APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 11期

基金：

新加坡国家研究基金会;

关键词：

harmony search algorithm; meta-heuristic optimization algorithms; optimization problems; clustering applications; PARTICLE SWARM OPTIMIZATION; TEXT FEATURE-SELECTION; KRILL HERD ALGORITHM; HYBRID; STRATEGY; PROTOCOL; DESIGN;

D O I：

10.3390/app10113827

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions.

引用

页数：26

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