{"id":"https://openalex.org/W6907324621","doi":"https://doi.org/10.21227/y2rj-xb73","title":"Bayesian CNN-BiLSTM and Vine-GMCM Based Probabilistic Forecasting of Hour-Ahead Wind Farm Power Outputs (Input dataset)","display_name":"Bayesian CNN-BiLSTM and Vine-GMCM Based Probabilistic Forecasting of Hour-Ahead Wind Farm Power Outputs (Input dataset)","publication_year":2022,"publication_date":"2022-01-18","ids":{"openalex":"https://openalex.org/W6907324621","doi":"https://doi.org/10.21227/y2rj-xb73"},"language":"en","primary_location":{"id":"doi:10.21227/y2rj-xb73","is_oa":true,"landing_page_url":"https://doi.org/10.21227/y2rj-xb73","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/y2rj-xb73","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zou, Mingzhe","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zou, Mingzhe","raw_affiliation_strings":["The University of Edinburgh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":null,"display_name":"\u0110akovi\u0107, Josip","orcid":null},"institutions":[{"id":"https://openalex.org/I181343428","display_name":"University of Zagreb","ror":"https://ror.org/00mv6sv71","country_code":"HR","type":"education","lineage":["https://openalex.org/I181343428"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"\u0110akovi\u0107, Josip","raw_affiliation_strings":["The University of Zagreb"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Zagreb","institution_ids":["https://openalex.org/I181343428"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"Probabilistic forecasting","score":0.6822999715805054},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6327000260353088},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.6116999983787537},{"id":"https://openalex.org/keywords/wind-power-forecasting","display_name":"Wind power forecasting","score":0.6021999716758728},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5573999881744385},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5343999862670898},{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.5329999923706055},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5169000029563904},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.4471000134944916}],"concepts":[{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.6822999715805054},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6327000260353088},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.6116999983787537},{"id":"https://openalex.org/C2781084341","wikidata":"https://www.wikidata.org/wiki/Q2583670","display_name":"Wind power forecasting","level":4,"score":0.6021999716758728},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5573999881744385},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5343999862670898},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.5329999923706055},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48399999737739563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48170000314712524},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.4471000134944916},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.29760000109672546},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.27480000257492065},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2581999897956848},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/y2rj-xb73","is_oa":true,"landing_page_url":"https://doi.org/10.21227/y2rj-xb73","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.21227/y2rj-xb73","is_oa":true,"landing_page_url":"https://doi.org/10.21227/y2rj-xb73","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[{"score":0.9036683440208435,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,25],"dataset":[1],"represents":[2],"the":[3,8,57,82,103,113,117,121],"input":[4],"data":[5,26,107],"on":[6],"which":[7,116],"article":[9],"Bayesian":[10],"CNN-BiLSTM":[11],"and":[12,38,42,52,67,93,98],"Vine-GMCM":[13],"Based":[14],"Probabilistic":[15],"Forecasting":[16],"of":[17,28,34,44,62,123],"Hour-Ahead":[18],"Wind":[19],"Farm":[20],"Power":[21],"Outputs,":[22],"is":[23],"based.":[24],"consist":[27],"a":[29,88,94],"two-year":[30],"hourly":[31],"time":[32],"series":[33],"measured":[35],"wind":[36,46],"speed":[37],"direction,":[39],"air":[40],"density,":[41],"production":[43],"two":[45,58,63],"farms":[47],"(WTs)":[48],"in":[49,72,81,112,115],"Croatia":[50],"(Bru\u0161ka":[51],"Jelinak).":[53],"In":[54],"addition":[55],"to":[56],"listed":[59],"WTs,":[60],"measurements":[61],"nearby":[64],"WTs":[65],"(Glunca":[66],"Zelengrad)":[68],"are":[69,77,85,127],"also":[70],"attached":[71],"training":[73,89],"files":[74],"(these":[75],"WPPs":[76],"not":[78],"directly":[79],"analyzed":[80],"article).":[83],"Datasets":[84],"divided":[86],"into":[87],"set":[90,96],"(4":[91],"WTs)":[92],"test":[95,104],"(Bruska":[97],"Jelinak":[99],"only).":[100],"To":[101],"extend":[102],"dataset,":[105],"additional":[106],"(extended_test":[108],"files)":[109],"were":[110],"used":[111,119],"paper,":[114],"timestamps":[118],"for":[120],"validation":[122],"proposed":[124],"forecasting":[125],"models":[126],"indicated.":[128]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
