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Titel Substorm onset identification using neural networks and Pi2 pulsations
VerfasserIn P. R. Sutcliffe
Medientyp Artikel
Sprache Englisch
ISSN 0992-7689
Digitales Dokument URL
Erschienen In: Annales Geophysicae ; 15, no. 10 ; Nr. 15, no. 10, S.1257-1264
Datensatznummer 250012972
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/angeo-15-1257-1997.pdf
 
Zusammenfassung
The pattern recognition capabilities of artificial neural networks (ANNs) have for the first time been used to identify Pi2 pulsations in magnetometer data, which in turn serve as indicators of substorm onsets and intensifications. The pulsation spectrum was used as input to the ANN and the network was trained to give an output of +1 for Pi2 signatures and -1 for non-Pi2 signatures. In order to evaluate the degree of success of the neural-network procedure for identifying Pi2 pulsations, the ANN was used to scan a number of data sets and the results compared with visual identification of Pi2 signatures. The ANN performed extremely well with a success rate of approximately 90% for Pi2 identification and a timing accuracy generally within 1 min compared to visual identification. A number of potential applications of the neural-network Pi2 scanning procedure are discussed.
 
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