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Sökning: id:"swepub:oai:DiVA.org:kth-307053" > Solar Energetic Par...

  • Aminalragia-Giamini, SigiavaSpace Applicat & Res Consultancy SPARC, Athens 10551, Greece.;Natl & Kapodistrian Univ Athens NKUA, Dept Phys, Athens 15772, Greece. (författare)

Solar Energetic Particle Event occurrence prediction using Solar Flare Soft X-ray measurements and Machine Learning

  • Artikel/kapitelEngelska2021

Förlag, utgivningsår, omfång ...

  • 2021-12-24
  • EDP Sciences,2021
  • printrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:DiVA.org:kth-307053
  • https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-307053URI
  • https://doi.org/10.1051/swsc/2021043DOI

Kompletterande språkuppgifter

  • Språk:engelska
  • Sammanfattning på:engelska

Ingår i deldatabas

Klassifikation

  • Ämneskategori:ref swepub-contenttype
  • Ämneskategori:art swepub-publicationtype

Anmärkningar

  • QC 20220110
  • The prediction of the occurrence of Solar Energetic Particle (SEP) events has been investigated over many years, and multiple works have presented significant advances in this problem. The accurate and timely prediction of SEPs is of interest to the scientific community as well as mission designers, operators, and industrial partners due to the threat SEPs pose to satellites, spacecrafts, and crewed missions. In this work, we present a methodology for the prediction of SEPs from the soft X-rays of solar flares associated with SEPs that were measured in 1 AU. We use an expansive dataset covering 25 years of solar activity, 1988-2013, which includes thousands of flares and more than two hundred identified and catalogued SEPs. Neural networks are employed as the predictors in the model, providing probabilities for the occurrence or not of a SEP, which are converted to yes/no predictions. The neural networks are designed using current and state-of-the-art tools integrating recent advances in the machine learning field. The results of the methodology are extensively evaluated and validated using all the available data, and it is shown that we achieve very good levels of accuracy with correct SEP occurrence prediction higher than 85% and correct no-SEP predictions higher than 92%. Finally, we discuss further work towards potential improvements and the applicability of our model in real-life conditions.

Ämnesord och genrebeteckningar

Biuppslag (personer, institutioner, konferenser, titlar ...)

  • Raptis, SavvasKTH,Rymd- och plasmafysik(Swepub:kth)u1po1x65 (författare)
  • Anastasiadis, AnastasiosInst Astron Astrophys Space Applicat & Remote Sen, Natl Observ Athens, Athens 15236, Greece. (författare)
  • Tsigkanos, AntonisSpace Applicat & Res Consultancy SPARC, Athens 10551, Greece. (författare)
  • Sandberg, IngmarSpace Applicat & Res Consultancy SPARC, Athens 10551, Greece. (författare)
  • Papaioannou, AthanasiosInst Astron Astrophys Space Applicat & Remote Sen, Natl Observ Athens, Athens 15236, Greece. (författare)
  • Papadimitriou, ConstantinosSpace Applicat & Res Consultancy SPARC, Athens 10551, Greece.;Natl & Kapodistrian Univ Athens NKUA, Dept Phys, Athens 15772, Greece. (författare)
  • Jiggens, PiersEuropean Space Agcy ESTEC ESA, European Res & Technol Ctr, NL-2200 AZ Noordwijk, Netherlands. (författare)
  • Aran, AngelsUniv Barcelona UB IEEC, Inst Ciencies Cosmos ICCUB, Dept Fis Quant & Astrofis, Barcelona 08028, Spain. (författare)
  • Daglis, Ioannis A.Natl & Kapodistrian Univ Athens NKUA, Dept Phys, Athens 15772, Greece.;Hellen Space Ctr, Athens 15231, Greece. (författare)
  • Space Applicat & Res Consultancy SPARC, Athens 10551, Greece.;Natl & Kapodistrian Univ Athens NKUA, Dept Phys, Athens 15772, Greece.Rymd- och plasmafysik (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:Journal of Space Weather and Space Climate: EDP Sciences112115-7251

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