Automatic Arrival Time Detection for Earthquakes Based on Stacked Denoising Autoencoder

The accurate detection of P-wave arrival time is imperative for determining the hypocenter location of an earthquake. However, precise detection of onset time becomes more difficult when the signal-to-noise ratio (SNR) of the seismic data is low, such as during microearthquakes. In this letter, a st...

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Veröffentlicht in:	IEEE Geoscience and Remote Sensing Letters Jg. 15; H. 11; S. 1687 - 1691
Hauptverfasser:	Saad, Omar M., Inoue, Koji, Shalaby, Ahmed, Samy, Lotfy, Sayed, Mohammed S.
Format:	Journal Article
Sprache:	Englisch Japanisch
Veröffentlicht:	Piscataway IEEE 01.11.2018 Institute of Electrical and Electronics Engineers (IEEE) The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Ambient noise Animal behavior Background noise Decoding Deep learning Detection Earthquakes Feature extraction Machine learning Microearthquakes Noise Noise measurement Noise reduction P-wave arrival time of earthquakes Seismic activity Seismic data Seismic waves Seismological data Signal to noise ratio stacked denoising autoencoder (SDAE) Waveforms
ISSN:	1545-598X, 1558-0571
Online-Zugang:	Volltext
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