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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107393


    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:[電機工程學系暨研究所] 會議論文

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