TRAINING THE MULTIFEEDBACK-LAYER NEURAL NETWORK USING THE PARTICLE SWARM OPTIMIZATION ALGORITHM

Aksu I. O., ÇOBAN R.

10th International Conference on Electronics, Computer and Computation (ICECCO), Ankara, Türkiye, 7 - 09 Kasım 2013, ss.172-175 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/icecco.2013.6718256
  • Basıldığı Şehir: Ankara
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.172-175
  • Çukurova Üniversitesi Adresli: Evet

Özet

In this study, the Multifeedback-Layer Neural Network (MFLNN) weights are trained by the Particle Swarm Optimization (PSO). This method (MFLNN-PSO) is applied to two different problems to prove accomplishment of the study. Firstly, a chaotic time series prediction problem is used to test the MFLNN-PSO. Also, the method is used for identification of a non-linear dynamic system. This study shows that the MFLNN-PSO can be used for dynamic system identification as well as controller design.