Comparison of adaptive-network-based fuzzy inference systems for bandwidth calculation of rectangular microstrip antennas

This paper presents a method based on adaptive-network-based fuzzy inference system (ANFIS) to compute the bandwidth of a rectangular microstrip antenna (MSA). Seven optimization algorithms, least-squares, Nelder–Mead, genetic, differential evolution, hybrid learning, particle swarm, and simulated annealing are used to determine optimally the design parameters of the ANFIS. The results of the ANFIS models show better agreement with the experimental results as compared to the results of previous methods available in the literature. When the performances of ANFIS models are compared with each other, the best result is obtained from the ANFIS model trained by the least-squares algorithm.