Abstract
AbstractUsing photospheric data obtained by vector magnetograph in Huairou Solar Observing Station of China, we have statistically studied the strength evolution of several magnetic nonpotentiality measures, along with a quantified parameter characterizing the active-region magnetic complexity – effective distance, and their relationship with associated flares during the latest 22nd and 23rd solar cycles. And the flare-prediction performance of these magnetic nonpotentiality and complexity parameters is verified by a machine learning technique.
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