Vol.7, No.4, November 2018.                                                                                                                                                                             ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Fuzzy Clustering with Particle Swarm Intelligence for Large Dataset Classification


Ashit Kumar Dutta


© 2018 Ashit Kumar Dutta, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 7, Issue 4, Pages 738-743, ISSN 2217-8309, DOI: 10.18421/TEM74-06, November 2018.


Received: 06 April 2018.
Accepted: 24 September 2018.
Published: 26 November 2018.




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.


Keywords –Swarm intelligence, Particle swarm optimization, Fuzzy clustering, Classification, Clustering.



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