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.
An observation-based Galactic Cosmic Ray(GCR)spectral model for heavy nuclei is developed.Zhao and Qin[J.Geophys.Res.Space Phys.118,1837(2013)]proposed an empirical elemental GCR spectra model for nuclear charge 5≤z≤28 over the energy range^30 to 500 Me V/nuc,which is proved to be successful in predicting yearly averaged GCR heavy nuclei spectra.Based on the latest highly statistically precise measurements from ACE/CRIS,a further elemental GCR model with monthly averaged spectra is presented.The model can reproduce the past and predict the future GCR intensity monthly by correlating model parameters with the continuous sunspot number(SSN)record.The effects of solar activity on GCR modulation are considered separately for odd and even solar cycles.Compared with other comprehensive GCR models,our modeling results are satisfyingly consistent with the GCR spectral measurements from ACE/SIS and IMP-8,and have comparable prediction accuracy as the Badhwar&O’Neill 2014 model.A detailed error analysis is also provided.Finally,the GCR carbon and iron nuclei fluxes for the subsequent two solar cycles(SC 25 and 26)are predicted and they show a potential trend in reduced flux amplitude,which is suspected to be relevant to possible weak solar cycles.
