Fuzzy set theory applied to CME importance classification

Abstract

In this paper, fuzzy set theory is applied to a quantitative way of assigning importance class to coronal mass ejection (CME) events based on four observed characteristics, i.e. velocity, span, mass and kinetic energy. The weights to be associated with each of the characteristics and the membership functions of belonging to one of the three importance classes are determined from the correlations between the characteristics and the CME morphology properties. A useful software of data reduction has been successfully compiled. The results show that the fuzzy comprehensive evaluation is better than the classic statistical analysis.