AUTOMATIC CLUSTERING WITH GLOBAL BEST ARTIFICIAL BEE COLONY ALGORITHM

OZTURK C., Hancer E., KARABOĞA D.

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, cilt.29, sa.4, ss.677-687, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 4
  • Basım Tarihi: 2014
  • Dergi Adı: JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.677-687
  • Anahtar Kelimeler: Automatic Clustering, Artificial Bee Colony, Particle Swarm Optimization, DIFFERENTIAL EVOLUTION, OPTIMIZATION
  • Erciyes Üniversitesi Adresli: Evet

Özet

Clustering, which is an important technique in analyzing data, is used in many fields, especially in image processing and statistical data analysis. In recent years, studies particularly on solving the clustering problem have been increased. In this paper, the global search ability of the artificial bee colony algorithm is improved and a vectorial search ability is integrated to the algorithm in order to solve the automatic clustering problem. The proposed clustering method is tested on the well- known benchmark datasets and images. The obtained results show that the performance of the proposed method is superior to the others and it can be applied to the automatic clustering problems.