PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Genovesi S., Mittra R., Monorchio A., Manara G. Particle swarm optimization for the design of frequency selective surfaces. Technical report, 2006.
 
 
Abstract
(English)
The particle swarm optimization (PSO) is a stochastic strategy that has recently found application to electromagnetic optimization problems. It is based on the behaviour of insect swarms and exploits the solution space by taking into account the experience of the single particle as well as that of the entire swarm. This combined and synergic use of information yields a promising tool for solving design problems that require the optimization of a relatively large number of parameters. In this paper, the problem of synthesizing Frequency Selective Surfaces (FSSs) is addressed by using a specifically derived particle swarm optimization procedure, which is able to handle, simultaneously, both real and binary parameters. Representative numerical examples are presented to demonstrate the effectiveness of the method. Finally, the performance of the PSO is compared with that of the genetic algorithm.
Subject Frequency selective surfaces
Artificial intelligence
Particle swarm optimization
J.2 Physical sciences and engineering


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional