Full-Disk Solar Flare Forecasting Model Based on Data Mining Method

Abstract EN

Solar flare is one of the violent solar eruptive phenomena; many solar flare forecasting models are built based on the properties of active regions.

However, most of these models only focus on active regions within 30° of solar disk center because of the projection effect.

Using cost sensitive decision tree algorithm, we build two solar flare forecasting models from the active regions within 30° of solar disk center and outside 30° of solar disk center, respectively.

The performances of these two models are compared and analyzed.

Merging these two models into a single one, we obtain a full-disk solar flare forecasting model.