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Neural Network for Coated/Uncoated Hydrosol ParticlesWhy Neural Network
- Accurately reproduce inherent optical properties (IOPs) for coated/uncoated hydrosol particles while reducing required disk space by 100x
- Provide IOP properties at least 100x faster than the advanced look-up-table
Document ID
20230002492
Acquisition Source
Langley Research Center
Document Type
Poster
Authors
Grant Sims (Universities Space Research Association Columbia, Maryland, United States)
Eduard Chemyakin (Science Systems & Applications, Inc. Hampton, VA, USA)
James Allen (University of Hawaii at Manoa Honolulu, Hawaii, United States)
Jacek Chowdhary (Columbia University New York, New York, United States)
Brian Cairns (Goddard Institute for Space Studies New York, New York, United States)
Snorre Stamnes (Langley Research Center Hampton, Virginia, United States)
Date Acquired
February 22, 2023
Subject Category
Computer Systems
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
Meeting: NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Science and Applications Team Meeting 2023
Location: San Diego, CA
Country: US
Start Date: February 27, 2023
End Date: March 1, 2023
Sponsors: National Aeronautics and Space Administration
Funding Number(s)
WBS: 564349.04.02.01.49
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
NASA Peer Committee

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