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1. Identity statement Reference Type Book Section Site mtc-m21c.sid.inpe.br Holder Code isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S Identifier 8JMKD3MGP3W34R/3RD7BSH Repository sid.inpe.br/mtc-m21c/2018/07.03.15.34   (restricted access) Last Update 2018:07.03.15.34.42 (UTC) simone Metadata Repository sid.inpe.br/mtc-m21c/2018/07.03.15.34.42 Metadata Last Update 2020:12.07.21.11.56 (UTC) administrator Secondary Key INPE--/ DOI 10.1007/978-3-319-54978-1_60 Citation Key DíscolaJúniorCecaFernRibe:2018:OpDaMi Title An optimized data mining method to support solar flare forecast Year 2018 Access Date 2024, May 08 Secondary Type PRE LI Number of Files 1 Size 436 KiB 2. Context Author 1 Díscola Júnior, Sérgio Luisir 2 Cecatto, José Roberto 3 Fernandes, Márcio Merino 4 Ribeiro, Marcela Xavier Resume Identifier 1 2 8JMKD3MGP5W/3C9JHJB Group 1 2 DIDAS-CGCEA-INPE-MCTIC-GOV-BR Affiliation 1 Universidade Federal de São Carlos (UFSCar) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Universidade Federal de São Carlos (UFSCar) 4 Universidade Federal de São Carlos (UFSCar) Author e-Mail Address 1 sergio.discola@dc.ufscar.br 2 jr.cecatto@inpe.br Editor Latifi, S. Book Title Information technology: new generations, advances in intelligent Publisher Springer Pages 467-474 History (UTC) 2018-07-03 15:35:07 :: simone -> administrator :: 2018 2020-12-07 21:11:56 :: administrator -> simone :: 2018 3. Content and structure Is the master or a copy? is the master Content Stage completed Transferable 1 Content Type External Contribution Version Type publisher Keywords solar flare forecasting times series data mining feature selection Abstract Historical Solar X-rays time series are employed to track solar activity and solar flares. High level of X-rays released during Solar Flares can interfere in telecommunication equipment operation. In this sense, it is important the development of computational methods to forecast Solar Flares analyzing the X-ray emissions. In this work, historical Solar X-rays time series sequences are employed to predict future Solar Flares using traditional classification algorithms. However, for large data sequences, the classification algorithms face the problem of dimensionality curse, where the algorithms performance and accuracy degrade with the increase in the sequence size. To deal with this problem, we proposed a method that employs feature selection to determine which time instants of a sequence should be considered by the mining process, reducing the processing time and increasing the accuracy of the mining process. Moreover, the proposed method also determines which are the antecedent time instants that most affect a future Solar Flare. Area CEA Arrangement An optimized data... doc Directory Content access source Directory Content there are no files agreement Directory Content agreement.html 03/07/2018 12:34 1.8 KiB  4. Conditions of access and use Language en Target File discola_optimized.pdf User Group simone Visibility shown Read Permission deny from all and allow from 150.163 Update Permission not transferred 5. Allied materials Next Higher Units 8JMKD3MGPCW/3ETR8EH Dissemination BNDEPOSITOLEGAL Host Collection urlib.net/www/2017/11.22.19.04 6. Notes Notes 14th International Conference on Information Technology Empty Fields archivingpolicy archivist callnumber city copyholder copyright creatorhistory descriptionlevel e-mailaddress edition format isbn issn label lineage mark mirrorrepository nextedition numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark serieseditor seriestitle session shorttitle sponsor subject tertiarymark tertiarytype translator url volume 7. Description control e-Mail (login) simone update

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