ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEM MODELS FOR COMPUTING THE CHARACTERISTIC IMPEDANCES OF AIR-SUSPENDED TRAPEZOIDAL AND RECTANGULAR-SHAPED MICROSHIELD LINES

In this article, adaptive-network-based frizzy inference system (ANFIS) models are proposed to compute the characteristic impedances of air-suspended trapezoidal-shaped microshield lines (AS-TSMLs) and air-suspended rectangular-shaped microshield lines (AS-RSMLs). The ANFIS is a fuzzy inference system implemented within the architecture and optimization procedure of adaptive networks. Four optimization algorithms, hybrid learning, simulated annealing, genetic, and least-squares, are used to determine optimally the design parameters of ANFIS. The characteristic impedance results of ANFIS models are in very good agreement with the results available in the literature. When the performances of ANFIS models are compared with each other, the best results are obtained from the ANFIS model trained by the hybrid learning algorithm. (C) 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 20-24, 2010; Published online in Wiley Inter-Science (www.interscience.wiley.com). DOI 10.1002/mop.24829