Automated flare prediction using the AdaBoost algorithm

Ru-Shi Lan, Yong Jiang, Liu-Guan Ding, Jian-Wei Yang


Abstract We propose a flare prediction method based on the AdaBoost algorithm, which constructs a strong prediction model from a combination of several basic models. Three predictors, extracted from the photospheric magnetograms, are applied as features to predict the occurrence of flares with a certain level over 24 hours following the time when the magnetogram is recorded. To demonstrate the effectiveness of the proposed method, comparisons of experimental results with respect to some existing methods are given. The results show that an improvement is achieved in predicting the occurrences of large flares.


Keywords Sun: flares — Sun: magnetic fields

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