Signal and noise detection in magnetotelluric data by the artificial neural network method

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dc.contributor.authorUluocak, Ebru Şengül
dc.contributor.authorUlugergerli, Emin U.
dc.contributor.authorGöktaş, Hilal
dc.date.accessioned2025-01-27T19:04:19Z
dc.date.available2025-01-27T19:04:19Z
dc.date.issued2013
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractIn this study artificial neural network method was used to classify noisy components in the MT method data. For this purpose a multi-layered, feed-foorward and back propagation model was employed. Noisy time windows were determined to an accuracy of 89% depending on the training data set. In addition, when all types of noise in the data are defined (synthetic data), all noisy time windows can be sellected and eliminated by artificial neural network method.Test results from synthetic and field data indicate that artificial neural network classification is succesfull in identifying and eliminating the noisy data windows compared to both visual inspection and conventional assessment methods.
dc.identifier.endpage72
dc.identifier.issn1301-2894
dc.identifier.issue1
dc.identifier.scopus2-s2.0-84877623032
dc.identifier.scopusqualityQ4
dc.identifier.startpage53
dc.identifier.urihttps://hdl.handle.net/20.500.12428/13905
dc.identifier.volume34
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherHacettepe Universitesi Yerbilmleri
dc.relation.ispartofYerbilimleri/ Earth Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250125
dc.subjectArtificial neural network; Magnetotelluric; Signal-noise detection; Time series
dc.titleSignal and noise detection in magnetotelluric data by the artificial neural network method
dc.title.alternativeYapay sinir a?ı yöntemi ile manyetotellürik veride sinyal ve gürültü ayırımı
dc.typeArticle

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