Uma Abordagem para Identificação de Padrões de Ocorrência de Eventos Solares Transientes Baseada no Fluxo de Múons

Abstract

The muon is an elementary particle with a negative charge, and is the most abundant charged component of cosmic radiation that penetrates deep into the Earth's soil. Analyzing the flow of muons that reaches our planet is important to identify solar eruptions that can cause harm to the population. This paper presents an approach based on sequence mining algorithms to automate the process of identifying frequent patterns in the captured muon stream. Experiments carried out show that the approach is capable of identifying eruptions by means of the identified frequent patterns.