A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications

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...

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Veröffentlicht in:Applied sciences Jg. 10; H. 11; S. 3827
Hauptverfasser: Abualigah, Laith, Diabat, Ali, Geem, Zong Woo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.06.2020
Schlagworte:
Algorithms
Analysis
Clustering
Clustering (Computers)
clustering applications
harmony search algorithm
Heuristic
Improvisation
Mathematical optimization
meta-heuristic optimization algorithms
Methods
Optimization algorithms
optimization problems
Optimization techniques
Population
Researchers
Swarm intelligence
Variables
United States
South Korea
United Arab Emirates
ISSN:2076-3417, 2076-3417
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Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:2076-3417
2076-3417
DOI:10.3390/app10113827