Novel Fuzzy Clustering Algorithm Based on Fireflies
- 10.2991/asei-15.2015.25How to use a DOI?
- Fuzzy c-means; Firefly; Chaos theory
Aiming at the existence of fuzzy C-means algorithm was sensitive to the initial clustering center and its shortcoming of easily plunged into local optimum ,this paper proposed a novel fuzzy clustering algorithm based on fireflies .The algorithm employed the chaos initialization individuals as the initial population .Then it utilized the improved fireflies as the accurately clustering center and received a new clustering center as the initial clustering center of fuzzy C-means .Thus it can overcome the fuzzy C-means’ sensitivity to the initial clustering center and solve the deficiency of easily falling into local optimum. Simulation experiment results based on UCI standard data sets show that the algorithm can avoid falling into local optimum and precocious, it also gets better performance and results compared with other algorithms.
- © 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 - Dan Li AU - Ke Luo AU - Zhen Sun PY - 2015/05 DA - 2015/05 TI - Novel Fuzzy Clustering Algorithm Based on Fireflies BT - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation PB - Atlantis Press SP - 112 EP - 116 SN - 2352-5401 UR - https://doi.org/10.2991/asei-15.2015.25 DO - 10.2991/asei-15.2015.25 ID - Li2015/05 ER -