Tora, HakanKapusuz, Kamil YavuzCan, SultanTora, HakanCan, SultanAirframe and Powerplant MaintenanceDepartment of Electrical & Electronics Engineering2024-10-062024-10-06201311330-36511848-6339[WOS-DOI-BELIRLENECEK-315]https://hdl.handle.net/20.500.14411/8624Can, Sultan/0000-0002-9001-0506This study proposes an artificial neural network (ANN) model in order to approximate the resonant frequencies of equilateral triangular patch antennas. The neural network structure applied here is trained and tested for both single-layer and double-layer antennas. It is shown upon experiment that the resonant frequencies obtained from the neural network are both more accurate than the calculated frequencies by formula and satisfactorily close to the measured frequencies. Results appear to be promising as per the available literature. This paper also may offer more efficient approach to developing antennas of such nature. While the total absolute error of 7 MHz and the average error of 0,09 % are achieved for single-layer antenna, the total absolute and average errors are 49 MHz and 0,07 % for the double-layered antenna, respectively.eninfo:eu-repo/semantics/closedAccessmicrostrip antennaneural networkresonant frequencyArticleQ4Q3206955960WOS:000328961800005