Yazar "Develi, İbrahim" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    AN APPLICATION OF ARTIFICIAL NEURAL NETWORK TO COMPUTE THE RESONANT FREQUENCY OF E-SHAPED COMPACT MICROSTRIP ANTENNAS
    (SLOVAK UNIV TECHNOLOGY, 2013) Akdağlı, Ali; Toktaş, Abdurrahim; Kayabaşı Ahmet; Develi, İbrahim
    An application of artificial neural network (ANN) based on multilayer perceptrons (MLP) to compute the resonant frequency of E-shaped compact microstrip antennas (ECMAs) is presented in this paper. The resonant frequencies of 144 ECMAs with different dimensions and electrical parameters were firstly determined by using IE3D((tm)) software based on the method of moments (MoM), then the ANN model for computing the resonant frequency was built by considering the simulation data. The parameters and respective resonant frequency values of 130 simulated ECMAs were employed for training and the remaining 14 ECMAs were used for testing the model. The computed resonant frequencies for training and testing by ANN were obtained with the average percentage errors (APE) of 0.257% and 0.523%, respectively. The validity and accuracy of the present approach was verified on the measurement results of an ECMA fabricated in this study. Furthermore, the effects of the slots loading method over the resonant frequency were investigated to explain the relationship between the slots and resonant frequency.
  • Küçük Resim Yok
    Öğe
    Computing resonant frequency of C-shaped compact microstrip antennas by using ANFIS
    (TAYLOR & FRANCIS LTD, 2015) Akdağlı, Ali; Kayabaşı, Ahmet; Develi, İbrahim
    In this work, the resonant frequency of C-shaped compact microstrip antennas (CCMAs) operating at UHF band is computed by using the adaptive neuro-fuzzy inference system (ANFIS). For this purpose, 144 CCMAs with various relative dielectric constants and different physical dimensions were simulated by the XFDTD software package based on the finite-difference time domain (FDTD) method. One hundred and twenty-nine CCMAs were employed for training, while the remaining 15 CCMAs were used for testing of the ANFIS model. Average percentage error (APE) values were obtained as 0.8413% and 1.259% for training and testing, respectively. In order to demonstrate its validity and accuracy, the proposed ANFIS model was also tested over the simulation data given in the literature, and APE was obtained as 0.916%. These results show that ANFIS can be successfully used to compute the resonant frequency of CCMAs.