Three new longitudinal magnetic field parameters are extracted from SOHO/MDI magnetograms to characterize properties of the stressed magnetic field in active regions, and their flare productivities are calculated for 1055 active regions. We find that the proposed parameters can be used to distinguish flaring samples from non-flaring samples. Using the long-term accumulated MDI data, we build the solar flare prediction model by using a data mining method. Furthermore, the decision boundary, which is used to divide flaring from non-flaring samples, is determined by the decision tree algorithm. Finally, the performance of the prediction model is evaluated by 10-fold cross validation technology. We conclude that an efficient solar flare prediction model can be built by the proposed longitudinal magnetic field parameters with the data mining method.
It is widely believed that the evolution of solar active regions leads to solar flares. However, information about the evolution of solar active regions is not employed in most existing solar flare forecasting models. In the current work, a short- term solar flare forecasting model is proposed, in which sequential sunspot data, in- cluding three days of information about evolution from active regions, are taken as one of the basic predictors. The sunspot area, the Mclntosh classification, the mag- netic classification and the radio flux are extracted and converted to a numerical for- mat that is suitable for the current forecasting model. Based on these parameters, the sliding-window method is used to form the sequential data by adding three days of information about evolution. Then, multi-layer perceptron and learning vector quanti- zation are employed to predict the flare level within 48 h. Experimental results indicate that the performance of the proposed flare forecasting model works better than previ- ous models.
Comparing the ESP/EVE/SDO flux data of 2011 Feb 6, with the counterparts of XRS/GOES and SEM/SOHO, we find that there is an enhancement that is not apparent in the two latter datasets. The enhancement, possibly regarded as a flare at first glimpse, nevertheless, does not involve an energy-release from the Sun. Based on the enhancement, we combine data from SXI/GOES 15 into a synthesized analysis, and concluded that it arises from a particle-associated enhancement in the channel that measures XUV radiation. Paradoxically, it seems to be somewhat of a particle-avalanching process. Prior to the event, a moderate geomagnetic storm took place. Subsequently, while the event is proceeding, a geomagnetic substorm is simultaneously observed. Therefore, the particles, though unidentified, are probably energetic electrons induced by substorm injection.
