| DOI | Resolve DOI: https://doi.org/10.1109/CSO.2009.367 |
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| Author | Search for: He, Si; Search for: Belacel, Nabil1; Search for: Hamam, Habib; Search for: Bouslimani, Yassine |
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| Affiliation | - National Research Council of Canada. NRC Institute for Information Technology
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| Format | Text, Article |
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| Conference | 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009, Sanya, Hainan, China, 24-26 April 2009 |
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| Subject | fuzzy set theory; genetic algorithms; pattern clustering |
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| Abstract | This paper applies the artificial fish swarm algorithm (AFSA) to fuzzy clustering. An improved AFSA with adaptive visual and adaptive step is proposed. AFSA enhances the performance of the fuzzy C-means (FCM) algorithm. A computational experiment shows that AFSA improved FCM out performs both the conventional FCM algorithm and the genetic algorithm (GA) improved FCM. |
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| Publication date | 2009 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NRC number | NRCC 50760 |
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| NPARC number | 15261133 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 2281de57-2ce5-451a-ab98-89434323e7e5 |
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| Record created | 2010-06-10 |
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| Record modified | 2020-04-16 |
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