Publication Details

Exploring k-PSO Algorithm for Clustering

HERMAN, D.; ORSÁG, F. Exploring k-PSO Algorithm for Clustering. Proceedings of the IASTED International Conference Artificial Intelligence and Applications (AIA 2013). Innsbruck: ACTA Press, 2013. p. 161-168. ISBN: 978-0-88986-943-1.

Czech title

Zkoumající k-PSO algoritmus shlukování

Type

conference paper

Language

English

Authors

Herman David, Ing. (PKO)
Orság Filip, Ing., Ph.D. (DITS)

Keywords

Swarm Intelligence, Clustering, SI, k-means, FCM, Exploring k-PSO

Abstract

Cluster analysis is a very popular approach to fully automatic search for patterns, data concepts, groups and clusters. It simplifies data representations and thus plays an important role in the process of knowledge acquisition. Data mining tasks require fast and accurate partition of data with many attributes. This requires new approach, which could deal better with these features. Methods based on the swarm intelligence present such approach to the cluster analysis. This article is a brief introduction to the optimization algorithms inspired by the natural world. It shows how these algorithms can be used in the cluster analysis and describes several up-to-date hybrid techniques combining PSO and k-means. Moreover, conceptually new hybrid algorithm based on the PSO and k-means is introduced and its efficiency and robustness are compared to the other algorithms using several datasets.

Published

2013

Pages

161–168

Proceedings

Proceedings of the IASTED International Conference Artificial Intelligence and Applications (AIA 2013)

ISBN

978-0-88986-943-1

Publisher

ACTA Press

Place

Innsbruck

BibTeX

@inproceedings{BUT103428,
  author="David {Herman} and Filip {Orság}",
  title="Exploring k-PSO Algorithm for Clustering",
  booktitle="Proceedings of the IASTED International Conference Artificial Intelligence and Applications (AIA 2013)",
  year="2013",
  pages="161--168",
  publisher="ACTA Press",
  address="Innsbruck",
  isbn="978-0-88986-943-1"
}