Genetic algorithm with artificial neural networks as its fitness function to design rectangular microstrip antenna on thick substrate

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Abstract

Over the years, genetic algorithms (GAs) have been applied in many applications. But the lack of a proper fitness function has been a hindrance to its widespread application in many cases. In this paper, a novel technique of using artificial neural networks (ANNs) as the fitness function of a genetic algorithm in order to calculate the design parameters of a thick substrate rectangular microstrip antenna is presented. A multilayer feed-forward neural network is used as the fitness function in a binary-coded genetic algorithm. The results obtained using this method are found to be closer to the experimental value, as compared to previous results obtained using the curve-fitting method. To validate this, the results are compared with the experimental values for five fabricated antennas. The results are in very good agreement with the experimental findings. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 44: 144–146, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20570

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