Prediction of solar activity with a neural network and its effect on orbit prediction

Details Prediction of solar activity with a neural network and its effect on orbit prediction Prediction of solar activity with a neural network and its effect on orbit prediction

Dec 1991

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1991jhatd..12..310w&link_type=abstract

Johns Hopkins APL Technical Digest (ISSN 0270-5214), vol. 12, Oct.-Dec. 1991, p. 310-317.

Computer Science

Mission Planning, Neural Nets, Satellite Tracking, Solar Activity, Space Station Freedom, Orbit Calculation, Prediction Analysis Techniques, Solar Flux, Steepest Descent Method

Scientific paper

Neural networks are presently shown to provide useful models for the highly complex variability of solar activity. Although the problem of solar activity prediction during maxima has not been satisfactorily resolved, the neural network generally performs better than the linear regression method in solar-activity prediction. Attention is given to the consequentiality of improved solar activity predictions via neural networks for predictions of the orbital position of satellites at orbital altitudes of less than 1000 km, for periods of up to 1 yr.

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