USAGE OF ANN AND ANFIS METHODS FOR COMPUTING RESONANT FREQUENCY OF SLOT-LOADED COMPACT MICROSTRIP ANTENNAS

作者：Kayabasi Ahmet^*; Akdagli Ali^*

来源：Journal of the Faculty of Engineering and Architecture of Gazi University, 2016, 31(1): 105-117.

• Microstrip antenna
• compact microstrip antenna
• resonant frequency
• artificial neural network
• adaptive neuro-fuzzy inference system

Microstrip antennas (MAs) have been widely used in the wireless communication systems since they have some superiorities over other microwave antennas. Compact microstrip antennas (CMAs) are obtained by modifying the conductor parts of MAs. CMAs have some advantages over the conventional MAs such as smaller size for the same resonant frequency. The models of artificial neural network (ANN) and/or adaptive neuro-fuzzy inference system (ANFIS) have been used for computing the resonant frequency of rectangular ring shaped CMA (RRCMA), C shaped CMA (CCMA), E shaped CMA (ECMA), H shaped CMA (HCMA) and L shaped CMA (LCMA) in the literature. In this survey study, the results obtained by the ANN and ANFIS models used for the resonant frequency computation of these slot loaded CMAs were compared with those of the other methods in the literature and it is seen that these methods are more successful. According to these results, it is seen that ANN and ANFIS networks which are the artificial intelligence techniques can be successfully used for computing the resonant frequency of slot loaded CMA. Moreover, when the ANN and ANFIS studies were investigated, it appears that they are faster and more effective than the other methods.

• 出版日期2016