Simple and accurate models based on adaptive-network-based fuzzy inference system (ANFIS) to compute the physical dimensions of open supported coplanar waveguides are presented. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems. Four optimization algorithms, hybrid learning, simulated annealing, least-squares, and genetic, are used to determine optimally the design parameters of the ANFIS. When the performances of ANFIS models are compared with each other, the best results are obtained from the ANFIS models trained by the hybrid learning algorithm. The results of ANFIS are compared with the results of the conformal mapping technique, the rigorous spectral-domain hybrid mode analysis, the improved spectral domain approach, the synthesis formulas, a full-wave electromagnetic simulator IE3D, and experimental works realized in this study.
This paper presents bees algorithm (BA) for null steering of linear antenna arrays by controlling only the element positions. The BA is an optimization algorithm inspired by the natural foraging behavior of honey bees to find the optimal solution. To show the versatility and flexibility of the proposed BA, several examples of Chebyshev array pattern with the imposed single, multiple and broad nulls are given. It is found that the nulling technique based on BA is capable of steering the array nulls precisely to the undesired interference directions. For practical consideration, the sensitivity of the produced patterns due to small variations of the element positions is also examined by rounding the element position values to the second decimal position.