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Multiobjective FET modeling using particle swarm optimization based on scattering parameters with Pareto optimal analysis

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dc.creator ÖZKAYA, Ufuk
dc.creator GÜNEŞ, Filiz
dc.date 2011-12-31T22:00:00Z
dc.date.accessioned 2020-10-06T11:25:56Z
dc.date.available 2020-10-06T11:25:56Z
dc.identifier dc97da93-53a4-4a03-a2b9-6b510efddd71
dc.identifier 10.3906/elk-1006-546
dc.identifier https://avesis.sdu.edu.tr/publication/details/dc97da93-53a4-4a03-a2b9-6b510efddd71/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/73811
dc.description In this paper, design-oriented field effect transistor (FET) models are produced. For this purpose, FET modeling is put forward as a constrained, multiobjective optimization problem. Two novel methods for multiobjective optimization are employed: particle swarm optimization (PSO) uses the single-objective function, which gathers all of the objectives as aggregating functions; and the nondominated sorting genetic (NSGA-II) sorts all of the trade-off solutions on the Pareto frontiers. The PSO solution is compared with the Pareto optimum solutions in the biobjective plane and the success of the first method is verified. Furthermore, the resulting PET models are compared with similar PET models from the literature, and thus a comparative study is put forward with respect to the success of the optimization algorithms and the performances and utilizations of the models in the amplification circuits.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Multiobjective FET modeling using particle swarm optimization based on scattering parameters with Pareto optimal analysis
dc.type info:eu-repo/semantics/article


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