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Sunspot Prediction Using Neural NetworksThe earliest systematic observance of sunspot activity is known to have been discovered by the Chinese in 1382 during the Ming Dynasty (1368 to 1644) when spots on the sun were noticed by looking at the sun through thick, forest fire smoke. Not until after the 18th century did sunspot levels become more than a source of wonderment and curiosity. Since 1834 reliable sunspot data has been collected by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Naval Observatory. Recently, considerable effort has been placed upon the study of the effects of sunspots on the ecosystem and the space environment. The efforts of the Artificial Intelligence Section of the Mission Planning and Analysis Division of the Johnson Space Center involving the prediction of sunspot activity using neural network technologies are described.
Document ID
19900016244
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
James Villarreal
(Johnson Space Center Houston, United States)
Paul Baffes
(Johnson Space Center Houston, United States)
Date Acquired
September 6, 2013
Publication Date
March 1, 1990
Publication Information
Publication: Third Annual Workshop on Space Operations Automation and Robotics (SOAR 1989)
Publisher: National Aeronautics and Space Administration
Subject Category
Solar Physics
Report/Patent Number
NASA-CP-3059
Meeting Information
Meeting: Third Annual Workshop on Space Operations Automation and Robotics (SOAR 1989)
Location: Houston, TX
Country: US
Start Date: July 25, 1989
End Date: July 27, 1989
Sponsors: United States Air Force, National Aeronautics and Space Administration
Accession Number
90N25560
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
NASA Technical Management
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