Solar Physics

, 294:6 | Cite as

Solar Flare Forecasting from Magnetic Feature Properties Generated by the Solar Monitor Active Region Tracker

  • Katarina DomijanEmail author
  • D. Shaun Bloomfield
  • François Pitié


We study the predictive capabilities of magnetic-feature properties (MF) generated by the Solar Monitor Active Region Tracker (SMART: Higgins et al. in Adv. Space Res.47, 2105, 2011) for solar-flare forecasting from two datasets: the full dataset of SMART detections from 1996 to 2010 which has been previously studied by Ahmed et al. (Solar Phys.283, 157, 2013) and a subset of that dataset that only includes detections that are NOAA active regions (ARs). The main contributions of this work are: we use marginal relevance as a filter feature selection method to identify the most useful SMART MF properties for separating flaring from non-flaring detections and logistic regression to derive classification rules to predict future observations. For comparison, we employ a Random Forest, Support Vector Machine, and a set of Deep Neural Network models, as well as lasso for feature selection. Using the linear model with three features we obtain significantly better results (True Skill Score: TSS = 0.84) than those reported by Ahmed et al. (Solar Phys.283, 157, 2013) for the full dataset of SMART detections. The same model produced competitive results (TSS = 0.67) for the dataset of SMART detections that are NOAA ARs, which can be compared to a broader section of flare-forecasting literature. We show that more complex models are not required for this data.


Flares, Forecasting Flares, Relation to Magnetic Field Active Regions, Magnetic Fields 


Disclosure of Potential Conflicts of Interest

The authors declare that they have no conflicts of interest.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsMaynooth UniversityMaynoothIreland
  2. 2.Department of Mathematics, Physics and Electrical EngineeringNorthumbria UniversityNewcastle Upon TyneUK
  3. 3.Department of Electronic and Electrical EngineeringTrinity College DublinDublinIreland

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