Previsão de atividade solar a partir da configuração dos campos magnéticos fotosféricos
Tipo
Dissertação
Data de publicação
2007-09-18
Periódico
Citações (Scopus)
Autores
Raffaelli, Tatiana Ferreira
Orientador
Silva, Adriana Valio Roque da
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Marengoni, Maurício
Costa, Joaquim Eduardo Rezende
Costa, Joaquim Eduardo Rezende
Programa
Engenharia Elétrica
Resumo
The existence of a highly reliable prediction system to detect the occurrence of large solar flares (class X) is still an unsolved problem. Despite many studies performed so far, no such a system has been found yet. In this work, we have developed a method using Bayesian Network - an Artificial Intelligence technique for the detection of giant solar flares. The Bayesian Networks software learned the relation among the variables that describe the sunspots within an active region and built a network with the relationships among them based on conditional probabilities. The studies were divided into two stages one to detect whether the sunspot would produce a big flare or not and another phase where some networks were built to discover the day the flare would occur. The first phase results were very satisfactory reaching a reliability of 77%. The second phase was more complex and the results were about 77% (with day constraints) and 54% (a wider range of days).
Descrição
Palavras-chave
Regiões ativas. Explosões solares. Redes Bayesianas. Fusão de informação. Sistemas de previsão. , Active Regions. Solar flares. Bayesian networks. Fusion of information. Forecast systems.
Assuntos Scopus
Citação
RAFFAELLI, Tatiana Ferreira. Previsão de atividade solar a partir da configuração dos campos magnéticos fotosféricos. 2007. 107 f. Dissertação (Mestrado em Engenharia Elétrica) - Universidade Presbiteriana Mackenzie, São Paulo, 2007.