A neural-network-based system for monitoring the aurora
Description
A series of Air Force Defense Meteorological Satellite Program satellites, collectively in continuous operation, measure precipitating particles in the range where most of the energy flux is carried. An algorithm was developed for automatically monitoring the high-latitude precipitation, including a neural-network-based identification of the source region of all precipitation observed. The result is an enormous and sophisticated data base, one use of which is to determine the appropriate mapping of ionospheric magnetic field lines into near-earth space. The data base is also being provided on a limited basis to the space physics community as a service. The system is a logical step in the development of a real-time capability to predict space weather. 19 refs
Additional details
Publishing Information
- Journal Title
- Johns Hopkins APL Technical Digest
- Journal Volume
- 11
- Series
- Johns Hopkins APL Tech. Dig.
- Journal Page Range
- 291-299
- ISSN
- 0270-5214
- CODEN
- JHADD
INIS
- Country of Publication
- United States
- Country of Input or Organization
- United States
- INIS RN
- 22055073
- Subject category
- S58: GEOSCIENCES;
- Descriptors DEI
- ALGORITHMS; AURORAE; CHARGED-PARTICLE PRECIPITATION; EARTH MAGNETOSPHERE; FORECASTING; INFORMATION SYSTEMS; INTERACTIONS; IONOSPHERE; MAGNETIC FIELDS; MONITORING; NEURAL NETWORKS; REAL TIME SYSTEMS; SATELLITES
- Descriptors DEC
- EARTH ATMOSPHERE