Proceedings of the 2015 International conference on Applied Science and Engineering Innovation

Clustering Algorithm Based on Artificial Bee Colony Optimization

Authors
Dandan Zhang, Ke Luo
Corresponding Author
Dandan Zhang
Available Online May 2015.
DOI
10.2991/asei-15.2015.28How to use a DOI?
Keywords
k-medoids clustering; granular computing; artificial bee colony; selection probability.
Abstract

After analyzing the disadvantages of sensitivity to the initial selection of the center, low clustering accuracy and the poor global search ability of k-medoids clustering algorithm, a clustering algorithm based on improved artificial bee colony (ABC) is proposed. By improving the initialization of bee colony, adjusting the search step dynamically with iteration increasing , and then introducing the selection probability based on sorting instead of depending on fitness directly, the ABC algorithm will quickly converge to global optimal. This paper will further optimize k-medoids to improve the performance of the clustering algorithm. The experimental results show that this algorithm can reduce the sensitive degree of the initial center selection and the noise, has high accuracy and strong stability.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
Series
Advances in Engineering Research
Publication Date
May 2015
ISBN
978-94-62520-94-3
ISSN
2352-5401
DOI
10.2991/asei-15.2015.28How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Dandan Zhang
AU  - Ke Luo
PY  - 2015/05
DA  - 2015/05
TI  - Clustering Algorithm Based on Artificial Bee Colony Optimization
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 126
EP  - 131
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.28
DO  - 10.2991/asei-15.2015.28
ID  - Zhang2015/05
ER  -