Parameter estimation for synthetic TEC surfaces by using Particle Swarm Optimization

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buir.contributor.authorArıkan, Orhan
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
dc.contributor.authorGökdaǧ, Y.E.en_US
dc.contributor.authorArikan F.en_US
dc.contributor.authorToker, C.en_US
dc.contributor.authorArıkan, Orhanen_US
dc.coverage.spatialMugla, Turkeyen_US
dc.date.accessioned2016-02-08T12:13:41Z
dc.date.available2016-02-08T12:13:41Z
dc.date.issued2012en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 18-20 April 2012en_US
dc.description.abstractIn this study, parameter estimation is made for global ionospheric Total Electron Content (TEC) on both noiseless and noisy synthetic surfaces by using modified Particle Swarm Optimization (PSO). In addition, the improvements made in the PSO algorithm to obtain better results are presented. Trend functions that best regionally and globally represent the quiet and distorted ionosphere are given. For noisy trend surfaces, additive white Gaussian noise is added on trend surfaces according to latitude. International GPS System stations (IGS) are used for regional sampling whereas TNPGN-Active stations are used for both regional and global sampling. A brief discussion of PSO and its improvements for modified PSO is provided. Performance and error criterias are determined for the results of noisy and noiseless dual-core Gaussian trend surfaces. © 2012 IEEE.en_US
dc.identifier.doi10.1109/SIU.2012.6204773en_US
dc.identifier.urihttp://hdl.handle.net/11693/28189
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2012.6204773en_US
dc.source.title2012 20th Signal Processing and Communications Applications Conference (SIU)en_US
dc.subjectAdditive White Gaussian noiseen_US
dc.subjectDual-coreen_US
dc.subjectGaussiansen_US
dc.subjectGlobal samplingen_US
dc.subjectInternational gps systemsen_US
dc.subjectIonospheric total electron contenten_US
dc.subjectModified particle swarm optimizationen_US
dc.subjectPSO algorithmsen_US
dc.subjectSynthetic surfacesen_US
dc.subjectTrend surfaceen_US
dc.subjectIonosphereen_US
dc.subjectParameter estimationen_US
dc.subjectSignal processingen_US
dc.subjectParticle swarm optimization (PSO)en_US
dc.titleParameter estimation for synthetic TEC surfaces by using Particle Swarm Optimizationen_US
dc.title.alternativeSentetik tei yüzeyleri için parçacik sürü optimizasyonu ile parametre kestirimien_US
dc.typeConference Paperen_US

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Parameter estimation for synthetic TEC surfaces by using Particle Swarm Optimization [Senteti̇k tei̇ yüzeyleri̇ i̇çi̇n parçacik sürü opti̇mi̇zasyonu i̇le parametre kesti̇ri̇mi̇].pdf
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