Adaptive neuro-fuzzy models for the quasi-static analysis of microstrip line

YILDIZ C. , Guney K. , TÜRKMEN M. , Kaya S.

MICROWAVE AND OPTICAL TECHNOLOGY LETTERS, cilt.50, sa.5, ss.1191-1196, 2008 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 50 Konu: 5
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1002/mop.23322
  • Sayfa Sayıları: ss.1191-1196


This article presents a new method based on adaptive neuro-fuzzy inference system (ANFIS) to calculate the effective permittivities and characteristic impedances of microstrip lines. The ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It has the advantages of expert knowledge of FISs and learning capability of artificial neural networks. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of AN-FIS. The results of ANFIS are compared with the results of the experimental works, quasi-static methods, and a commercial electromagnetic simulator IE3D. There is very good agreement among the results of ANFIS models and quasi-static methods, IE3D, and experimental works. (C) 2008 Wiley Periodicals, Inc.