Neural network prediction of solar energetic proton events with long lead times

Details Neural network prediction of solar energetic proton events with long lead times Neural network prediction of solar energetic proton events with long lead times

Mar 2002

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002esasp.477..517p&link_type=abstract

In: Proceedings of the Second Solar Cycle and Space Weather Euroconference, 24 - 29 September 2001, Vico Equense, Italy. Editor:

Computer Science

1

Solar Energetic Protons

Scientific paper

The high-energy particles that are emitted by the sun during Solar Proton Events (SPEs) pose a serious hazard to interplanetary and near-earth spacecraft causing damage to electronics, spurious signals and a general disruption of spacecraft operations. An analysis of GOES X-rays and full disk solar radio flux prior to proton events has revealed significant differences compared to times at which no proton events occurred. Selecting predictor variables using the F-statistic, neural network models have been generated which use data from tens of days prior to SPEs to predict their occurrence 48 hours in advance with a 65% success rate. This is an improvement in lead time of an order of magnitude over current SPE prediction models.

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