Using deep learning to predict solar explosions using magnetograms
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Palavras-chave

Solar explosions
Deep learning
Classification.

Como Citar

FERNANDES, Matheus Evers Rodrigues; GRADVOHL, Andre Leon Sampaio. Using deep learning to predict solar explosions using magnetograms. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 26, 2019. DOI: 10.20396/revpibic2620181036. Disponível em: https://econtents.bc.unicamp.br/eventos/index.php/pibic/article/view/1036. Acesso em: 28 mar. 2024.

Resumo

Solar activities, especially solar explosions, have a significant impact on some important technologies used on Earth, e.g., energy transmission networks and communications. Depending on the class of the explosion, the consequences can be hazardous. Therefore, when forecasting of solar explosions, earlier we can take actions to mitigate their impact on the affected technologies on Earth. In this work, we applied Deep Learning techniques to classify solar magnetograms, which indicate the class of a solar explosion. The classification of such images may help to anticipate the phenomenon. The results show a 97% of accuracy for the magnetograms classification.

https://doi.org/10.20396/revpibic2620181036
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