Comparison of Steady-State Genetic Algorithm and Asynchronous Particle Swarm Optimization on Inverse Scattering of a Partially Immersed Metallic Cylinder

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Title:	Comparison of Steady-State Genetic Algorithm and Asynchronous Particle Swarm Optimization on Inverse Scattering of a Partially Immersed Metallic Cylinder
Authors:	Sun, Chi Hsien;Huang, Chung-Hsin;Li, Ching-Lieh;Chiu, En-Nung
Keywords:	Inverse Scattering;Asynchronous Particle Swarm Optimization;Partially Immersed Conductor
Date:	2014-05-12
Issue Date:	2016-08-18 13:39:38 (UTC+8)
Abstract:	The inverse problem under consideration is to reconstruct the characteristic of scatterer from the scattering E field. Steady-state genetic algorithm (SSGA) and asynchronous particle swarm optimization (APSO) are stochastic-type optimization approach that aims to minimize a cost function between measurements and computer-simulated data. Thus, the shape of metallic cylinder can be obtained by minimizing the objective function. After an integral formulation, a discretization using the method of moment (MoM) is applied. Numerical results indicate that the asynchronous particle swarm optimization (APSO) outperforms steady-state genetic algorithm (SSGA) in terms of reconstruction accuracy and convergence speed.
Relation:	2014 International Symposium on Electromagnetic Compatibility (EMC14) , pp.817-820
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Proceeding

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