Application of Machine Learning Methods in Recurrent Sunspot Groups Identification

Sunspots – observable patches on the Sun where intense magnetic fields loop up through the surface – play significant role in research of solar activity. One of the difficulties faced by researcher is restricted visibility of the Sun – one can see only half of the solar surface from the Earth. Especially strong solar activity is connected with large sunspot groups that are supposed to be visible during more than one solar rotation. Hence continuous observation of such groups is impossible and the problem of long-lived (recurrent) sunspot groups identification arises. Today exist applications of data analysis and machine learning methods to this problem. The most prolonged database of sunspot group areas is the Royal Greenwich Observatory catalogue began in 1874 (it contains also descriptions of some groups supposed to be recurrent). We will show one of the identification algorithms, results of its application and comparison with other approaches.