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  1. University of Computer Studies, Yangon
  2. Journals

Comparative Study of Fuzzy PSO (FPSO) Clustering Algorithm and Fuzzy C-Means (FCM) Clustering Algorithm

http://hdl.handle.net/20.500.12678/0000004358
http://hdl.handle.net/20.500.12678/0000004358
71e526c5-78ce-45a3-b93e-cc77e469cb7a
d106be05-937e-4297-aff6-d2f4f2cb5fcf
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NJPSC NJPSC 2019 Proceedings-pages-62-67.pdf (624 Kb)
Publication type
Article
Upload type
Publication
Title
Title Comparative Study of Fuzzy PSO (FPSO) Clustering Algorithm and Fuzzy C-Means (FCM) Clustering Algorithm
Language en_US
Publication date 2019-03
Authors
Oo, Phyo Phyo
Htoon, Ei Chaw
Description
Swarm intelligence that mimic the naturalcollective intelligence to solve the computationalproblem has emerged and widely used in data mining.Particle swarm optimization (PSO) is a kind of swarmintelligence algorithm. Fuzzy clustering is animportant research in several real-world applications.Fuzzy particle swarm optimization (FPSO) is a fuzzyclustering algorithm that can be optimized with the useof PSO algorithm to get global optima. Fuzzy c-means(FCM) is one of the most popular fuzzy clusteringtechniques. In this paper, FPSO and FCM clusteringalgorithms will be implemented. These two methodswere compared in term of execution times and fuzzyobjective function ( �� ) by using datasets namely IrisPlants, Breast Cancer and Wine from UCI (Universityof California) Machine Learning repository.
Keywords
Fuzzy Clustering, Particle Swarm Optimization, Fuzzy Particle Swarm Optimization (FPSO), Fuzzy C-means (FCM)
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/2297
Journal articles
National Journal of Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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