Parameter estimation for synthetic TEC surfaces by using Particle Swarm Optimization
buir.contributor.orcid | Arıkan, Orhan|0000-0002-3698-8888 | en_US |
dc.contributor.author | Gökdaǧ, Y.E. | en_US |
dc.contributor.author | Arikan F. | en_US |
dc.contributor.author | Toker, C. | en_US |
dc.contributor.author | Arıkan, Orhan | en_US |
dc.contributor.bilkentauthor | Arıkan, Orhan | |
dc.coverage.spatial | Mugla, Turkey | en_US |
dc.date.accessioned | 2016-02-08T12:13:41Z | |
dc.date.available | 2016-02-08T12:13:41Z | |
dc.date.issued | 2012 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description | Date of Conference: 18-20 April 2012 | en_US |
dc.description.abstract | In 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.doi | 10.1109/SIU.2012.6204773 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/28189 | |
dc.language.iso | Turkish | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/SIU.2012.6204773 | en_US |
dc.source.title | 2012 20th Signal Processing and Communications Applications Conference (SIU) | en_US |
dc.subject | Additive White Gaussian noise | en_US |
dc.subject | Dual-core | en_US |
dc.subject | Gaussians | en_US |
dc.subject | Global sampling | en_US |
dc.subject | International gps systems | en_US |
dc.subject | Ionospheric total electron content | en_US |
dc.subject | Modified particle swarm optimization | en_US |
dc.subject | PSO algorithms | en_US |
dc.subject | Synthetic surfaces | en_US |
dc.subject | Trend surface | en_US |
dc.subject | Ionosphere | en_US |
dc.subject | Parameter estimation | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Particle swarm optimization (PSO) | en_US |
dc.title | Parameter estimation for synthetic TEC surfaces by using Particle Swarm Optimization | en_US |
dc.title.alternative | Sentetik tei yüzeyleri için parçacik sürü optimizasyonu ile parametre kestirimi | en_US |
dc.type | Conference Paper | en_US |
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