title: SPE dose prediction using locally weighted regression.
abstract: When astronauts are outside Earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events. The total dose received from a major solar particle event in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be reduced with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train, and provides predictions as accurate as the neural network models that were used previously.
authors.affiliation: Department of Nuclear Engineering, The University of Tennessee, Knoxville, TN 37996-2300, USA. jhines2@utk.edu
authors.forename: J W
authors.initials: JW
authors.lastname: Hines
authors.forename: L W
authors.initials: LW
authors.lastname: Townsend
authors.forename: T F
authors.initials: TF
authors.lastname: Nichols
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003359:Cosmic Radiation; D006801:Humans; D018499:Linear Energy Transfer; D008422:Materials Testing; D015233:Models, Statistical; D016571:Neural Networks, Computer; D011829:Radiation Dosage; D011832:Radiation Injuries / Q000517:prevention & control; D011835:Radiation Protection / Q000379:methods*; D011874:Radiometry / Q000379:methods*; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012542:Scattering, Radiation; D019445:Solar Activity; D013026:Space Flight