{"id":"https://openalex.org/W3098870503","doi":"https://doi.org/10.1080/01605682.2021.1880297","title":"The uncertainty estimation of feature-based forecast combinations","display_name":"The uncertainty estimation of feature-based forecast combinations","publication_year":2021,"publication_date":"2021-03-08","ids":{"openalex":"https://openalex.org/W3098870503","doi":"https://doi.org/10.1080/01605682.2021.1880297","mag":"3098870503"},"language":"en","primary_location":{"id":"doi:10.1080/01605682.2021.1880297","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01605682.2021.1880297","pdf_url":null,"source":{"id":"https://openalex.org/S169988927","display_name":"Journal of the Operational Research Society","issn_l":"0160-5682","issn":["0160-5682","1476-9360"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319703","host_organization_name":"Palgrave Macmillan","host_organization_lineage":["https://openalex.org/P4310319703","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Palgrave Macmillan","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Operational Research Society","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1908.02891","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xiaoqian Wang","orcid":"https://orcid.org/0000-0003-4827-496X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqian Wang","raw_affiliation_strings":["Beihang University, Beijing, China","BeiHang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"BeiHang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038747906","display_name":"Yanfei Kang","orcid":"https://orcid.org/0000-0001-8769-6650"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfei Kang","raw_affiliation_strings":["Beihang University, Beijing, China","BeiHang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"BeiHang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090115427","display_name":"Fotios Petropoulos","orcid":"https://orcid.org/0000-0003-3039-4955"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Fotios Petropoulos","raw_affiliation_strings":["University of Bath, Bath, UK","Management"],"affiliations":[{"raw_affiliation_string":"University of Bath, Bath, UK","institution_ids":["https://openalex.org/I51601045"]},{"raw_affiliation_string":"Management","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Feng Li","orcid":"https://orcid.org/0000-0002-4248-9778"},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Li","raw_affiliation_strings":["Central University of Finance and Economics, Beijing, China","[Central University of Finance and Economics]"],"affiliations":[{"raw_affiliation_string":"Central University of Finance and Economics, Beijing, China","institution_ids":["https://openalex.org/I137867983"]},{"raw_affiliation_string":"[Central University of Finance and Economics]","institution_ids":["https://openalex.org/I137867983"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I137867983"],"apc_list":null,"apc_paid":null,"fwci":0.1794,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50221252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"73","issue":"5","first_page":"979","last_page":"993"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8080540895462036},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6815717220306396},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.6714171171188354},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5871788263320923},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5627676844596863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5425688624382019},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5285507440567017},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5251895189285278},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4416438639163971},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4370030462741852},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1271667778491974},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09816482663154602}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8080540895462036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6815717220306396},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6714171171188354},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5871788263320923},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5627676844596863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5425688624382019},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5285507440567017},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5251895189285278},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4416438639163971},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4370030462741852},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1271667778491974},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09816482663154602},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1080/01605682.2021.1880297","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01605682.2021.1880297","pdf_url":null,"source":{"id":"https://openalex.org/S169988927","display_name":"Journal of the Operational Research Society","issn_l":"0160-5682","issn":["0160-5682","1476-9360"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319703","host_organization_name":"Palgrave Macmillan","host_organization_lineage":["https://openalex.org/P4310319703","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Palgrave Macmillan","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Operational Research Society","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1908.02891","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.02891","pdf_url":"https://arxiv.org/pdf/1908.02891","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3098870503","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1908.02891.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:RePEc:taf:tjorxx:v:73:y:2022:i:5:p:979-993","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/01605682.2021.1880297","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:purehost.bath.ac.uk:openaire/de742c8e-8b77-496c-b5ca-bb508179bbbf","is_oa":false,"landing_page_url":"https://researchportal.bath.ac.uk/en/publications/de742c8e-8b77-496c-b5ca-bb508179bbbf","pdf_url":null,"source":{"id":"https://openalex.org/S4377196294","display_name":"Pure (University of Bath)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I51601045","host_organization_name":"University of Bath","host_organization_lineage":["https://openalex.org/I51601045"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wang, X, Kang, Y, Petropoulos, F & Li, F 2022, 'The uncertainty estimation of feature-based forecast combinations', Journal of the Operational Research Society, vol. 73, no. 5, pp. 979-993. https://doi.org/10.1080/01605682.2021.1880297","raw_type":"article"},{"id":"doi:10.48550/arxiv.1908.02891","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1908.02891","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1908.02891","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.02891","pdf_url":"https://arxiv.org/pdf/1908.02891","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1084572967","display_name":null,"funder_award_id":"2019YFB1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1318648466","display_name":null,"funder_award_id":"11501587","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3214160367","display_name":null,"funder_award_id":"No. 11","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3931792713","display_name":null,"funder_award_id":"No. 1170","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4798598715","display_name":null,"funder_award_id":"2019YFB1404600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5167091242","display_name":null,"funder_award_id":"No. 1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7491067892","display_name":null,"funder_award_id":"11701022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321125","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1970860694","https://openalex.org/W1977698057","https://openalex.org/W1989367490","https://openalex.org/W2016210396","https://openalex.org/W2025720061","https://openalex.org/W2037097753","https://openalex.org/W2047445560","https://openalex.org/W2055311466","https://openalex.org/W2058874953","https://openalex.org/W2068448163","https://openalex.org/W2131077880","https://openalex.org/W2147028502","https://openalex.org/W2151554678","https://openalex.org/W2158808535","https://openalex.org/W2162174678","https://openalex.org/W2540346834","https://openalex.org/W2581984534","https://openalex.org/W2787031726","https://openalex.org/W2883806129","https://openalex.org/W2909973217","https://openalex.org/W2963507686","https://openalex.org/W2999406809","https://openalex.org/W3030907323"],"related_works":["https://openalex.org/W2965436710","https://openalex.org/W3190174726","https://openalex.org/W3189088612","https://openalex.org/W2909973217","https://openalex.org/W2883806129","https://openalex.org/W3190704708","https://openalex.org/W3126056062","https://openalex.org/W2016166233","https://openalex.org/W3141046848","https://openalex.org/W2082374132","https://openalex.org/W2052928274","https://openalex.org/W3006338851","https://openalex.org/W2159651898","https://openalex.org/W2037097753","https://openalex.org/W187478754","https://openalex.org/W2071984058","https://openalex.org/W2973060168","https://openalex.org/W3114824067","https://openalex.org/W2065410941","https://openalex.org/W164056561"],"abstract_inverted_index":{"Forecasting":[0],"is":[1],"an":[2,10,70,84],"indispensable":[3],"element":[4],"of":[5,18,87,110,128,134],"operational":[6],"research":[7],"(OR)":[8],"and":[9,33,37,58,76,89],"important":[11],"aid":[12],"to":[13,98],"planning.":[14],"The":[15],"accurate":[16],"estimation":[17],"the":[19,52,59,99,114],"forecast":[20],"uncertainty":[21],"facilitates":[22],"several":[23],"operations":[24],"management":[25,36],"activities,":[26],"predominantly":[27],"in":[28,31,132],"supporting":[29],"decisions":[30],"inventory":[32],"supply":[34],"chain":[35],"effectively":[38],"setting":[39],"safety":[40],"stocks.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45],"introduce":[46],"a":[47,77,107,125],"feature-based":[48],"framework,":[49],"which":[50],"links":[51],"relationship":[53],"between":[54],"time":[55,95,111],"series":[56,96,112],"features":[57],"interval":[60,66],"forecasting":[61],"performance":[62],"into":[63],"providing":[64],"reliable":[65],"forecasts.":[67],"We":[68,102],"propose":[69],"optimal":[71],"threshold":[72],"ratio":[73],"searching":[74],"algorithm":[75],"new":[78],"weight":[79],"determination":[80],"mechanism":[81],"for":[82,93],"selecting":[83],"appropriate":[85],"subset":[86],"models":[88],"assigning":[90],"combination":[91],"weights":[92],"each":[94],"tailored":[97],"observed":[100],"features.":[101],"evaluate":[103],"our":[104,121],"approach":[105,122],"using":[106],"large":[108],"set":[109],"from":[113],"M4":[115],"competition.":[116],"Our":[117],"experiments":[118],"show":[119],"that":[120],"significantly":[123],"outperforms":[124],"wide":[126],"range":[127],"benchmark":[129],"models,":[130],"both":[131],"terms":[133],"point":[135],"forecasts":[136],"as":[137,139],"well":[138],"prediction":[140],"intervals.":[141]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}