{"id":"https://openalex.org/W7135012423","doi":"https://doi.org/10.1109/clei67442.2025.11420753","title":"Solar Flare Prediction Using Multivariate Time Series and Cost-Sensitive Machine Learning","display_name":"Solar Flare Prediction Using Multivariate Time Series and Cost-Sensitive Machine Learning","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7135012423","doi":"https://doi.org/10.1109/clei67442.2025.11420753"},"language":null,"primary_location":{"id":"doi:10.1109/clei67442.2025.11420753","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei67442.2025.11420753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 LI Latin American Computer Conference (CLEI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037487628","display_name":"Ricardo Zorzal Davila","orcid":null},"institutions":[{"id":"https://openalex.org/I1282368058","display_name":"International Foundation for Electoral Systems","ror":"https://ror.org/033esc660","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1282368058"]},{"id":"https://openalex.org/I4210160371","display_name":"Instituto Federal do Esp\u00edrito Santo","ror":"https://ror.org/05rshs160","country_code":"BR","type":"funder","lineage":["https://openalex.org/I4210160371"]}],"countries":["BR","US"],"is_corresponding":false,"raw_author_name":"Ricardo Zorzal Davila","raw_affiliation_strings":["Instituto Federal do Esp&#x00ED;rito Santo,PPComp, IFES Campus Serra,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Federal do Esp&#x00ED;rito Santo,PPComp, IFES Campus Serra,Brazil","institution_ids":["https://openalex.org/I4210160371","https://openalex.org/I1282368058"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064310592","display_name":"Filipe Mutz","orcid":"https://orcid.org/0000-0002-2951-9207"},"institutions":[{"id":"https://openalex.org/I51235708","display_name":"Universidade Federal do Esp\u00edrito Santo","ror":"https://ror.org/05sxf4h28","country_code":"BR","type":"education","lineage":["https://openalex.org/I51235708"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Filipe Wall Mutz","raw_affiliation_strings":["Universidade Federal do Esp&#x00ED;rito Santo,Vit&#x00F3;ria-ES,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Esp&#x00ED;rito Santo,Vit&#x00F3;ria-ES,Brazil","institution_ids":["https://openalex.org/I51235708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128809120","display_name":"Jefferson O. Andrade","orcid":null},"institutions":[{"id":"https://openalex.org/I1282368058","display_name":"International Foundation for Electoral Systems","ror":"https://ror.org/033esc660","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1282368058"]},{"id":"https://openalex.org/I4210160371","display_name":"Instituto Federal do Esp\u00edrito Santo","ror":"https://ror.org/05rshs160","country_code":"BR","type":"funder","lineage":["https://openalex.org/I4210160371"]}],"countries":["BR","US"],"is_corresponding":false,"raw_author_name":"Jefferson O. Andrade","raw_affiliation_strings":["Instituto Federal do Esp&#x00ED;rito Santo,PPComp, IFES Campus Serra,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Federal do Esp&#x00ED;rito Santo,PPComp, IFES Campus Serra,Brazil","institution_ids":["https://openalex.org/I4210160371","https://openalex.org/I1282368058"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128850122","display_name":"Karin Satie Komati","orcid":null},"institutions":[{"id":"https://openalex.org/I1282368058","display_name":"International Foundation for Electoral Systems","ror":"https://ror.org/033esc660","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1282368058"]},{"id":"https://openalex.org/I4210160371","display_name":"Instituto Federal do Esp\u00edrito Santo","ror":"https://ror.org/05rshs160","country_code":"BR","type":"funder","lineage":["https://openalex.org/I4210160371"]}],"countries":["BR","US"],"is_corresponding":false,"raw_author_name":"Karin Satie Komati","raw_affiliation_strings":["Instituto Federal do Esp&#x00ED;rito Santo,PPComp, IFES Campus Serra,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Federal do Esp&#x00ED;rito Santo,PPComp, IFES Campus Serra,Brazil","institution_ids":["https://openalex.org/I4210160371","https://openalex.org/I1282368058"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72480508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10251","display_name":"Solar and Space Plasma Dynamics","score":0.7439000010490417,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10251","display_name":"Solar and Space Plasma Dynamics","score":0.7439000010490417,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.07109999656677246,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10159","display_name":"Ionosphere and magnetosphere dynamics","score":0.057500001043081284,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/solar-flare","display_name":"Solar flare","score":0.705299973487854},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6061999797821045},{"id":"https://openalex.org/keywords/flare","display_name":"Flare","score":0.5838000178337097},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5681999921798706},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.5419999957084656},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5105000138282776},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5099999904632568},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.4749000072479248},{"id":"https://openalex.org/keywords/lag","display_name":"Lag","score":0.439300000667572}],"concepts":[{"id":"https://openalex.org/C185001636","wikidata":"https://www.wikidata.org/wiki/Q119830","display_name":"Solar flare","level":2,"score":0.705299973487854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6220999956130981},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6061999797821045},{"id":"https://openalex.org/C2779588948","wikidata":"https://www.wikidata.org/wiki/Q628261","display_name":"Flare","level":2,"score":0.5838000178337097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.570900022983551},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5681999921798706},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.5419999957084656},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5105000138282776},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5099999904632568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4936000108718872},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.4749000072479248},{"id":"https://openalex.org/C75778745","wikidata":"https://www.wikidata.org/wiki/Q342626","display_name":"Lag","level":2,"score":0.439300000667572},{"id":"https://openalex.org/C2777618391","wikidata":"https://www.wikidata.org/wiki/Q1483757","display_name":"Solar power","level":3,"score":0.4025000035762787},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3815999925136566},{"id":"https://openalex.org/C151325931","wikidata":"https://www.wikidata.org/wiki/Q584093","display_name":"Space weather","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.3555000126361847},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.3061999976634979},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3003999888896942},{"id":"https://openalex.org/C2987767877","wikidata":"https://www.wikidata.org/wiki/Q352862","display_name":"Time lag","level":3,"score":0.296099990606308},{"id":"https://openalex.org/C170061395","wikidata":"https://www.wikidata.org/wiki/Q5468164","display_name":"Forecast skill","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.25940001010894775},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/clei67442.2025.11420753","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei67442.2025.11420753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 LI Latin American Computer Conference (CLEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7187985181808472,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2946010671","https://openalex.org/W3021885473","https://openalex.org/W3026268188","https://openalex.org/W3035773482","https://openalex.org/W4210481843","https://openalex.org/W4318185503","https://openalex.org/W4327663846","https://openalex.org/W4360596441","https://openalex.org/W4391930102","https://openalex.org/W4407914220"],"related_works":[],"abstract_inverted_index":{"Prediction":[0],"of":[1,10,23,121,126,133],"solar":[2,37,143],"flares":[3,38],"is":[4,84],"critical":[5],"for":[6,141],"minimizing":[7],"the":[8,21,75,95,99,131],"impact":[9],"space":[11],"weather":[12],"on":[13],"communication":[14],"and":[15,33,47,62,65,70,108,123,137],"power":[16],"systems.":[17],"This":[18],"study":[19],"explores":[20],"application":[22],"machine":[24],"learning":[25,83],"models\u2014Long":[26],"Short-Term":[27],"Memory":[28],"(LSTM),":[29],"Random":[30],"Forest":[31],"(RF),":[32],"XGBoost":[34],"(XGB)\u2014to":[35],"forecast":[36],"using":[39,86,103],"multivariate":[40],"time":[41],"series":[42],"data":[43],"derived":[44],"from":[45],"SHARP":[46],"GOES.":[48],"The":[49],"experimental":[50],"setup":[51],"systematically":[52],"varies":[53],"two":[54],"key":[55],"temporal":[56,135],"parameters:":[57],"window":[58,107],"size":[59],"(12,":[60,68],"24,":[61,69],"48":[63,71],"hours)":[64],"prediction":[66,111],"lag":[67],"hours).":[72],"To":[73],"address":[74],"strong":[76],"class":[77,89,138],"imbalance":[78,139],"in":[79],"flare":[80,144],"data,":[81],"cost-sensitive":[82],"incorporated":[85],"a":[87,104,109,116],"sample-based":[88],"weighting":[90],"strategy.":[91],"Results":[92],"demonstrate":[93],"that":[94],"LSTM":[96],"model":[97],"achieves":[98],"best":[100],"performance":[101],"when":[102],"short":[105],"12-hour":[106,110],"lag,":[112],"reaching":[113],"89%":[114],"accuracy,":[115],"True":[117],"Skill":[118],"Statistic":[119],"(TSS)":[120],"0.6949,":[122],"an":[124],"F1-score":[125],"0.6873.":[127],"These":[128],"findings":[129],"emphasize":[130],"importance":[132],"short-term":[134],"dependencies":[136],"mitigation":[140],"improving":[142],"forecasting":[145],"performance.":[146]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-13T00:00:00"}
