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Predicting Astronaut Radiation Doses From Large Solar Particle Events Using Artificial Intelligence The University of Tennessee

SAE Technical Papers (1906-current) Available online

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Format:
Conference/Event
Author/Creator:
Tehrani, Nazila H., author.
Conference Name:
International Conference On Environmental Systems (1999-07-12 : Denver, Colorado, United States)
Language:
English
Physical Description:
1 online resource
Place of Publication:
Warrendale, PA SAE International 1999
Summary:
For deep space missions, a major concern is the occurrence of large solar particle events. In this work a dynamic, new type of artificial neural network called a Sliding Time Delay Neural Network that is capable of accurately predicting total dose for an event, from several input doses early in the event, is presented. The network can update its total dose predictions during the event as new input data are received. Results from testing indicate that the network can predict total doses from large events that are outside the training set to within 4% very early in the event
Notes:
Vendor supplied data
Publisher Number:
1999-01-2172
Access Restriction:
Restricted for use by site license

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