Affiliations: [a] Department of Electrical – Electronics
Engineering, Faculty of Engineering, Mersin University, Yenisehir, Mersin,
Turkey | [b] Department of Information Technologies, Mersin
University, Yenisehir, Mersin, Turkey | [c] Department of Electronics and Automation, Silifke
– Tasucu Vocational School of Selcuk University, Silifke, Mersin,
Turkey | [d] Department of Software Engineering, Faculty of Tarsus
Technology, Mersin University, Tarsus, Mersin, Turkey | [e] Department of Physics, Science and Letter Faculty,
Mersin University, Yenisehir, Mersin, Turkey
Correspondence:
[*]
Corresponding author: Ali Akdagli, Department of Electrical
– Electronics Engineering, Faculty of Engineering, Mersin University,
Ciftlikkoy, Yenisehir, 33343, Mersin, Turkey. Tel.: +90 324 361 0001; Fax: +90
324 361 0001; E-mail: akdagli@mersin.edu.tr
Abstract: In this work, a model constructed with the adaptive neuro –
fuzzy inference system (ANFIS) for estimating the resonant frequency of
rectangular ring compact microstrip antennas (RRCMAs) in UHF band is proposed.
A total of 108 RRCMAs having different parameters related to the antenna
dimensions and dielectric substrate were simulated with the help of
electromagnetic packaged software IE3D™ based on method of moment (MoM)
to generate the data pool for training and test processes of the ANFIS model.
While 96 RRCMAs were employed for training, the remainders were used for test
the ANFIS model. The resonant frequencies were computed with the average
percentage errors (APE) as 0.014% and 0.666% for training and test,
respectively. The accuracy of proposed model was successfully demonstrated by
comparing with the results of a method over the simulated data previously
published in the literature. Further to inspect the validity of the ANFIS
model, a RRCMA operating at 2.44 GHz was designed and fabricated for this work,
and the accurate results concerning the resonant frequency were achieved.
