Signal and noise detection in magnetotelluric data by the artificial neural network method
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Tarih
2013
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Hacettepe Universitesi Yerbilmleri
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In 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.
Açıklama
Anahtar Kelimeler
Artificial neural network; Magnetotelluric; Signal-noise detection; Time series
Kaynak
Yerbilimleri/ Earth Sciences
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
34
Sayı
1
