Exploring comprehensible classification rules from trained neural networks integrated with a time-varying binary particle swarm optimizer

ÖZBAKIR L., Delice Y.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, cilt.24, sa.3, ss.491-500, 2011 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Sayı: 3
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.engappai.2010.11.008
  • Dergi Adı: ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.491-500
  • Anahtar Kelimeler: Artificial neural networks, Particle swarm optimization, Rule extraction, Data mining, Classification, EXTRACTING RULES, ROUGH SETS, ALGORITHM
  • Erciyes Üniversitesi Adresli: Evet

Özet

Purpose: Extracting comprehensible classification rules is the most emphasized concept in data mining researches. In order to obtain accurate and comprehensible classification rules from databases, a new approach is proposed by combining advantages of artificial neural networks (ANN) and swarm intelligence.