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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Volume 15, issue 10
Ann. Geophys., 15, 1257–1264, 1997
https://doi.org/10.1007/s00585-997-1257-x
© European Geosciences Union 1997
Ann. Geophys., 15, 1257–1264, 1997
https://doi.org/10.1007/s00585-997-1257-x
© European Geosciences Union 1997

  31 Oct 1997

31 Oct 1997

Substorm onset identification using neural networks and Pi2 pulsations

P. R. Sutcliffe P. R. Sutcliffe
  • Hermanus Magnetic Observatory, P.O. Box 32, Hermanus 7200, South Africa

Abstract. 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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