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A Novel Feature Selection Method for Solar Flare Forecasting

  • Ashwini Nagaraj Shenoy*
  • , Deepu Vijayasenan
  • , Raghavendra S. Bobbi
  • , Sreejith Padinhatteeri
  • , H. N. Adithya
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Large solar flares (SFs) can disrupt radio communication and harm instruments and astronauts. Hence, it's crucial to predict SFs. However, the mechanism that triggers SFs is not yet known. We only have several physical features believed to be related to the process. This makes choosing the most impactful features for SF production important. We investigate a feature selection method based on the weights learned by a linear classifier. We use the Spaceweather HMI Active Region Patch (SHARP) summary parameters based on the Solar Dynamics Observatory's Helioseismic and Magnetic Imager data records. The records are from May 2010 to December 2019.

Original languageEnglish
Title of host publication2024 IEEE Space, Aerospace and Defence Conference, SPACE 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages656-659
Number of pages4
ISBN (Electronic)9798350367386
DOIs
Publication statusPublished - 2024
Event2024 IEEE Space, Aerospace and Defence Conference, SPACE 2024 - Bangalore, India
Duration: 22-07-202423-07-2024

Publication series

Name2024 IEEE Space, Aerospace and Defence Conference, SPACE 2024

Conference

Conference2024 IEEE Space, Aerospace and Defence Conference, SPACE 2024
Country/TerritoryIndia
CityBangalore
Period22-07-2423-07-24

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Aerospace Engineering
  • Instrumentation

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