Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/8687
AuthorsGiudicepietro, F.* 
Esposito, A.* 
D'Auria, L.* 
Martini, M.* 
Scarpetta, S.* 
TitleAutomatic analysis of seismic data by using Neural Networks: applications to Italian volcanoes
Issue Date2008
PublisherIstituto Nazionale di Geofisica e Vulcanologia
URIhttp://hdl.handle.net/2122/8687
ISBN978-88-89972-09-0
KeywordsNeural Networks
Italian volcanoes
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring 
AbstractThe availability of the new computing techniques allows to perform advanced analysis in near real time, improving the seismological monitoring systems, which can extract more significant information from the raw data in a really short time. However, the correct identification of the events remains a critical aspect for the reliability of near real time automatic analysis. We approach this problem by using Neural Networks (NN) for discriminating among the seismic signals recorded in the Neapolitan volcanic area (Vesuvius, Phlegraean Fields). The proposed neural techniques have been also applied to other sets of seismic data recorded in Stromboli volcano. The obtained results are very encouraging, giving 100% of correct classification for some transient signals recorded at Vesuvius and allowing the clustering of the large dataset of VLP events recorded at Stromboli volcano.
Appears in Collections:Book chapters

Files in This Item:
File Description SizeFormat 
NN_Warner_2008.pdf498 kBAdobe PDFView/Open
Show full item record

Page view(s)

87
checked on Apr 27, 2017

Download(s)

63
checked on Apr 27, 2017

Google ScholarTM

Check