Use of particle swarm optimization to obtain designing parameters from data set of frequency selective surface

To get designing parameters of a frequency selective surface is very difficult and time consuming. This work suggests a method where different designing parameters with its respective resulting factors are kept in a data set from where accurate designing factors can be found for a desired frequency. Particle swarm optimization technique is suggested for proper searching. This algorithm can search efficiently and find approximate value of the desired parameters if the accurate one is not present in the data set. This paper deals with a data set. It includes different periodicities in a two dimensional array of circular patch type frequency selective surfaces and the resonating frequencies of the structures. Particle swarm optimization program efficiently searches from this data set and shows periodicity for a desired frequency.