An Analysis of the Effects of SVM Parameters on the Dead-Time System Modeling

KABAOĞLU N., Kabaoglu R. O.

ELECTRICA, cilt.18, sa.1, ss.1-5, 2018 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 1
  • Basım Tarihi: 2018
  • Doi Numarası: 10.5152/iujeee.2018.1801
  • Dergi Adı: ELECTRICA
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.1-5
  • İstanbul Üniversitesi Adresli: Evet

Özet

Modeling a dead-time system is a common issue in engineering applications. To address this issue, existing research has employed neural networks and fuzzy logic-based intelligent systems. Herein, a dead-time system modeled with the aid of support vector machine regression, which has a good generalization feature, was investigated. The performance of the method proposed herein was examined with different parameters in linear and nonlinear dead-time systems.