ANFIS MODELS FOR SYNTHESIS OF OPEN SUPPORTED COPLANAR WAVEGUIDES


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

NEURAL NETWORK WORLD, vol.23, no.6, pp.553-569, 2013 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 6
  • Publication Date: 2013
  • Doi Number: 10.14311/nnw.2013.23.033
  • Title of Journal : NEURAL NETWORK WORLD
  • Page Numbers: pp.553-569

Abstract

Simple and accurate models based on adaptive-network-based fuzzy inference system (ANFIS) to compute the physical dimensions of open supported coplanar waveguides are presented. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems. Four optimization algorithms, hybrid learning, simulated annealing, least-squares, and genetic, are used to determine optimally the design parameters of the ANFIS. When the performances of ANFIS models are compared with each other, the best results are obtained from the ANFIS models trained by the hybrid learning algorithm. The results of ANFIS are compared with the results of the conformal mapping technique, the rigorous spectral-domain hybrid mode analysis, the improved spectral domain approach, the synthesis formulas, a full-wave electromagnetic simulator IE3D, and experimental works realized in this study.