Fuzzy Clustering with Particle Swarm Intelligence for Large Dataset Classification
Journal: TEM JOURNAL - Technology, Education, Management, Informatics (Vol.7, No. 4)Publication Date: 2018-11-26
Authors : Ashit Kumar Dutta;
Page : 738-743
Keywords : Swarm intelligence; Particle swarm optimization; Fuzzy clustering; Classification; Clustering;
Abstract
The most challenging problem in data mining is deriving knowledge from large dataset. Existing methods have better performance in medium – scale dataset but the level of performance degrades in large datasets. Swarm intelligence (SI) is a computational method to solve complex problems inspired from biological phenomena like flock of birds, shoal of fish, herd of sheep and swarm of bees. The ant colony optimization is the multi-agent system solving of problems through cooperation like ants. Particle swarm optimization (PSO) is one of the methods successfully implemented with fuzzy concepts and solved complex problems. The objective of the research is to classify the large dataset using fuzzy clustering with PSO. The experiment results proved that the proposed method is more effective and produces optimum accuracy.
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Last modified: 2018-12-01 07:42:48