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Microstrip antennas (MAs) have been widely used in the wireless communication systems since they have some superiorities over other microwave antennas. Compact microstrip antennas (CMAs) are obtained by modifying the conductor parts of MAs. CMAs have some advantages over the conventional MAs such as smaller size for the same resonant frequency. The models of artificial neural network (ANN) and/or adaptive neuro-fuzzy inference system (ANFIS) have been used for computing the resonant frequency of rectangular ring shaped CMA (RRCMA), C shaped CMA (CCMA), E shaped CMA (ECMA), H shaped CMA (HCMA) and L shaped CMA (LCMA) in the literature. In this survey study, the results obtained by the ANN and ANFIS models used for the resonant frequency computation of these slot loaded CMAs were compared with those of the other methods in the literature and it is seen that these methods are more successful. According to these results, it is seen that ANN and ANFIS networks which are the artificial intelligence techniques can be successfully used for computing the resonant frequency of slot loaded CMA. Moreover, when the ANN and ANFIS studies were investigated, it appears that they are faster and more effective than the other methods. [ABSTRACT FROM AUTHOR]

In this paper a simple and efficient heuristic search method based on the artificial bee colony (ABC) algorithm is presented and used for the optimal power ow (OPF) problem in power systems with static VAR compensator (SVC) devices. The total generation cost of a power system with SVC devices (which improve the voltage stability at load buses) is optimally minimized with the use of ABC. The ABC, which is based on the foraging behavior of honey bees searching for the best food source, is a recently proposed optimization algorithm. The performance of the presented ABC algorithm was tested and verified on the IEEE 11-bus and IEEE 30-bus power systems by comparing it with several other optimization methods. Furthermore, ABC is used not only for optimizing the total generation cost and active power loss, but also for improving the voltage stability of the 22-bus power system in Turkey. Our results illustrate that ABC can successfully be used to solve nonlinear problems related to power systems. [ABSTRACT FROM AUTHOR]