Using Support Vector Machine (SVM) and Ionospheric Total Electron Content (TEC) Data for Solar Flare Predictions

Keyphrases

• Solar Flare Prediction 100%
• Solar Flares 100%
• Support Vector Machine 100%
• Content Data 100%
• Ionospheric Total Electron Content 100%
• Machine Learning Techniques 50%
• M-class 50%
• Skill Score 50%
• β-Class 50%
• Space Weather Events 50%
• C Class 50%
• Total Electron Content 50%
• Heidke Skill Score 50%
• Machine Learning 25%
• Work-related 25%
• X-ray 25%
• C(X) 25%
• Distribution Pattern 25%
• X-class 25%
• Space Weather 25%
• X-ray Irradiation 25%
• Ionosphere 25%
• Sub-daily 25%
• Score Accuracy 25%
• True Skill Statistic 25%
• Ionization Effect 25%
• Space Weather Research 25%
• Ultraviolet Rays 25%
• Precision-recall 25%
• X-ray Bursts 25%
• Solar X-ray Flares 25%
• Time Series Forecasting 25%
• Extreme Ultraviolet 25%
• Past Distribution 25%
• Multivariate Data Analysis Techniques 25%

Earth and Planetary Sciences

• Solar Flare 100%
• Ionospherics 100%
• Total Electron Content 100%
• Support Vector Machine 100%
• Space Weather 57%
• Machine Learning 42%
• X Ray 42%
• Time Series 28%

Physics

• Solar Flare 100%