{"id":"https://openalex.org/W2775339876","doi":"https://doi.org/10.1109/smc.2017.8123210","title":"Ensemble learning for forecasting main meteorological parameters","display_name":"Ensemble learning for forecasting main meteorological parameters","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2775339876","doi":"https://doi.org/10.1109/smc.2017.8123210","mag":"2775339876"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2017.8123210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2017.8123210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5058278718","display_name":"Petros Karvelis","orcid":"https://orcid.org/0000-0002-0483-4868"},"institutions":[{"id":"https://openalex.org/I4210159397","display_name":"Technological Educational Institute of Epirus","ror":"https://ror.org/04brn7x66","country_code":"GR","type":"education","lineage":["https://openalex.org/I4210159397"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Petros Karvelis","raw_affiliation_strings":["Department of Computer Engineering Technological Educational Institute of Epirus, Laboratory of Knowledge and Intelligent Computing, Arta, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering Technological Educational Institute of Epirus, Laboratory of Knowledge and Intelligent Computing, Arta, Greece","institution_ids":["https://openalex.org/I4210159397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057807510","display_name":"Stavros Kolios","orcid":"https://orcid.org/0000-0001-5084-9801"},"institutions":[{"id":"https://openalex.org/I120729142","display_name":"Research Academic Computer Technology Institute","ror":"https://ror.org/021nszj63","country_code":"GR","type":"facility","lineage":["https://openalex.org/I120729142","https://openalex.org/I4210154149"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stavros Kolios","raw_affiliation_strings":["Computer Technology Institute & Press \u201cDiophantus\u201d, Patras, Greece","Computer Technology Institute & Press \"Diophantus\", Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Computer Technology Institute & Press \u201cDiophantus\u201d, Patras, Greece","institution_ids":["https://openalex.org/I120729142"]},{"raw_affiliation_string":"Computer Technology Institute & Press \"Diophantus\", Patras, Greece","institution_ids":["https://openalex.org/I120729142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022376997","display_name":"George Georgoulas","orcid":"https://orcid.org/0000-0001-9701-4203"},"institutions":[{"id":"https://openalex.org/I190632392","display_name":"Lule\u00e5 University of Technology","ror":"https://ror.org/016st3p78","country_code":"SE","type":"education","lineage":["https://openalex.org/I190632392"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"George Georgoulas","raw_affiliation_strings":["Control Engineering Division of the Department of Computer, Lulea University of Technology, Lulea, Sweden"],"affiliations":[{"raw_affiliation_string":"Control Engineering Division of the Department of Computer, Lulea University of Technology, Lulea, Sweden","institution_ids":["https://openalex.org/I190632392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009967164","display_name":"Chrysostomos Stylios","orcid":"https://orcid.org/0000-0002-2888-6515"},"institutions":[{"id":"https://openalex.org/I4210159397","display_name":"Technological Educational Institute of Epirus","ror":"https://ror.org/04brn7x66","country_code":"GR","type":"education","lineage":["https://openalex.org/I4210159397"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Chrysostomos Stylios","raw_affiliation_strings":["Department of Computer Engineering Technological Educational Institute of Epirus, Laboratory of Knowledge and Intelligent Computing, Arta, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering Technological Educational Institute of Epirus, Laboratory of Knowledge and Intelligent Computing, Arta, Greece","institution_ids":["https://openalex.org/I4210159397"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058278718"],"corresponding_institution_ids":["https://openalex.org/I4210159397"],"apc_list":null,"apc_paid":null,"fwci":1.1467,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.80676756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.7268545031547546},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7188774347305298},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.6664509773254395},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6388044357299805},{"id":"https://openalex.org/keywords/weather-forecasting","display_name":"Weather forecasting","score":0.6236370205879211},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5425472855567932},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5418837666511536},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.47628918290138245},{"id":"https://openalex.org/keywords/weather-prediction","display_name":"Weather prediction","score":0.4552042782306671},{"id":"https://openalex.org/keywords/technology-forecasting","display_name":"Technology forecasting","score":0.45218366384506226},{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"Probabilistic forecasting","score":0.4391452372074127},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.4335877299308777},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.42742636799812317},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.19274139404296875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09257802367210388}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7268545031547546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7188774347305298},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.6664509773254395},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6388044357299805},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.6236370205879211},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5425472855567932},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5418837666511536},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.47628918290138245},{"id":"https://openalex.org/C2987469573","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather prediction","level":2,"score":0.4552042782306671},{"id":"https://openalex.org/C161657586","wikidata":"https://www.wikidata.org/wiki/Q1203326","display_name":"Technology forecasting","level":2,"score":0.45218366384506226},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.4391452372074127},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.4335877299308777},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.42742636799812317},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.19274139404296875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09257802367210388},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc.2017.8123210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2017.8123210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1556459174","https://openalex.org/W1573647811","https://openalex.org/W1678356000","https://openalex.org/W1861272876","https://openalex.org/W1971623340","https://openalex.org/W1992561742","https://openalex.org/W1995947858","https://openalex.org/W2019216225","https://openalex.org/W2050148124","https://openalex.org/W2059642600","https://openalex.org/W2060823820","https://openalex.org/W2068394775","https://openalex.org/W2084175761","https://openalex.org/W2093643917","https://openalex.org/W2095499778","https://openalex.org/W2102041666","https://openalex.org/W2107641306","https://openalex.org/W2120012334","https://openalex.org/W2125294618","https://openalex.org/W2142827986","https://openalex.org/W2145237692","https://openalex.org/W2395249678","https://openalex.org/W2487087946","https://openalex.org/W2488758846","https://openalex.org/W2549363851","https://openalex.org/W2617606220","https://openalex.org/W2911964244","https://openalex.org/W4248018214","https://openalex.org/W4298304654","https://openalex.org/W4299397599","https://openalex.org/W6633355566","https://openalex.org/W6634147026","https://openalex.org/W6712620249"],"related_works":["https://openalex.org/W2990134330","https://openalex.org/W4293349030","https://openalex.org/W1563787591","https://openalex.org/W3127901020","https://openalex.org/W1623003057","https://openalex.org/W1585017814","https://openalex.org/W1969424709","https://openalex.org/W3121928891","https://openalex.org/W1545465591","https://openalex.org/W2551806350"],"abstract_inverted_index":{"The":[0,67,87],"significant":[1],"role":[2],"of":[3,13,22,25,40,69,85,90,100,103,115],"predicting":[4],"weather":[5],"conditions":[6],"in":[7],"daily":[8],"life,":[9],"the":[10,20,45,101],"new":[11],"era":[12],"innovative":[14],"machine":[15],"learning":[16,52,105],"approaches":[17,53],"along":[18],"with":[19,71],"availability":[21],"high":[23,28],"volumes":[24],"data":[26],"and":[27,118,124],"computer":[29],"performance":[30],"capabilities,":[31],"creates":[32],"increasing":[33],"perspectives":[34],"for":[35,48,64,82,106],"novel":[36],"improved":[37],"short-range":[38],"forecasting":[39,49,113],"main":[41,88],"meteorological":[42],"parameters.":[43],"Among":[44],"various":[46],"algorithms":[47],"parameters,":[50],"ensemble":[51,104,120],"are":[54,122],"able":[55],"to":[56,73,95],"generate":[57],"simple":[58],"models":[59,75,121],"which":[60],"provide":[61,96],"accurate":[62],"predictions":[63],"regression":[65],"problems.":[66,86],"advantage":[68],"ensembles":[70],"respect":[72],"single":[74,117],"is":[76,94],"that":[77],"they":[78],"perform":[79],"remarkably":[80],"well":[81],"a":[83,116],"variety":[84],"aim":[89],"this":[91,111],"ongoing":[92],"research":[93],"some":[97],"preliminary":[98],"assessment":[99],"applicability":[102],"wind":[107],"speed":[108],"forecasting.":[109],"In":[110],"work,":[112],"results":[114],"two":[119],"presented":[123],"compared.":[125]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
