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http://dx.doi.org/10.5303/JKAS.2014.47.6.209

FORECAST OF SOLAR PROTON EVENTS WITH NOAA SCALES BASED ON SOLAR X-RAY FLARE DATA USING NEURAL NETWORK  

Jeong, Eui-Jun (Department of Astronomy and Space Science, Kyung Hee University)
Lee, Jin-Yi (Department of Astronomy and Space Science, Kyung Hee University)
Moon, Yong-Jae (Department of Astronomy and Space Science, Kyung Hee University)
Park, Jongyeop (School of Space Research, Kyung Hee University)
Publication Information
Journal of The Korean Astronomical Society / v.47, no.6, 2014 , pp. 209-214 More about this Journal
Abstract
In this study we develop a set of solar proton event (SPE) forecast models with NOAA scales by Multi Layer Perceptron (MLP), one of neural network methods, using GOES solar X-ray flare data from 1976 to 2011. Our MLP models are the first attempt to forecast the SPE scales by the neural network method. The combinations of X-ray flare class, impulsive time, and location are used for input data. For this study we make a number of trials by changing the number of layers and nodes as well as combinations of the input data. To find the best model, we use the summation of F-scores weighted by SPE scales, where F-score is the harmonic mean of PODy (recall) and precision (positive predictive value), in order to minimize both misses and false alarms. We find that the MLP models are much better than the multiple linear regression model and one layer MLP model gives the best result.
Keywords
space weather; solar proton event; solar X-ray flare; neural network; multi layer perceptron;
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