Neural models for the elliptic- and circular-shaped microshield lines

KAYA S., TÜRKMEN M., GÜNEY K., YILDIZ C.

Progress In Electromagnetics Research B, cilt.6, ss.169-181, 2008 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 6
  • Basım Tarihi: 2008
  • Doi Numarası: 10.2528/pierb08031216
  • Dergi Adı: Progress In Electromagnetics Research B
  • Derginin Tarandığı İndeksler: Scopus, Applied Science & Technology Source, Compendex, INSPEC
  • Sayfa Sayıları: ss.169-181
  • Erciyes Üniversitesi Adresli: Evet

Özet

© 2008, Electromagnetics Academy.This article presents a new approach based on artificial neural networks (ANNs) to calculate the characteristic parameters of elliptic and circular-shaped microshield lines. Six learning algorithms, bayesian regularization (BR), Levenberg-Marquardt (LM), quasi- Newton (QN), scaled conjugate gradient (SCG), resilient propagation (RP), and conjugate gradient of Fletcher-Reeves (CGF), are used to train the ANNs. The neural results are in very good agreement with the results reported elsewhere. When the performances of neural models are compared with each other, the best and worst results are obtained from the ANNs trained by the BR and CGF algorithms, respectively.