{"id":"https://openalex.org/W2043132213","doi":"https://doi.org/10.1057/palgrave.jors.2602073","title":"Some evidence on forecasting time-series with support vector machines","display_name":"Some evidence on forecasting time-series with support vector machines","publication_year":2005,"publication_date":"2005-11-14","ids":{"openalex":"https://openalex.org/W2043132213","doi":"https://doi.org/10.1057/palgrave.jors.2602073","mag":"2043132213"},"language":"en","primary_location":{"id":"doi:10.1057/palgrave.jors.2602073","is_oa":false,"landing_page_url":"https://doi.org/10.1057/palgrave.jors.2602073","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":"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/A5101471712","display_name":"James V. Hansen","orcid":"https://orcid.org/0000-0001-9785-2776"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"J V Hansen","raw_affiliation_strings":["Marriott School of Management, Brigham Young University Provo UT USA"],"affiliations":[{"raw_affiliation_string":"Marriott School of Management, Brigham Young University Provo UT USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080595326","display_name":"James B. McDonald","orcid":"https://orcid.org/0000-0002-3919-5058"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J B McDonald","raw_affiliation_strings":["Department of EconomicsBrigham Young University Provo UT USA","Department of Economics, Brigham Young University, Provo, USA"],"affiliations":[{"raw_affiliation_string":"Department of EconomicsBrigham Young University Provo UT USA","institution_ids":["https://openalex.org/I100005738"]},{"raw_affiliation_string":"Department of Economics, Brigham Young University, Provo, USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108102795","display_name":"R. David Nelson","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R D Nelson","raw_affiliation_strings":["Marriott School of Management, Brigham Young University Provo UT USA"],"affiliations":[{"raw_affiliation_string":"Marriott School of Management, Brigham Young University Provo UT USA","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101471712"],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":null,"apc_paid":null,"fwci":2.1084,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.88107395,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"57","issue":"9","first_page":"1053","last_page":"1063"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9980999827384949,"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":0.9980999827384949,"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":0.9916999936103821,"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"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9914000034332275,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.945499062538147},{"id":"https://openalex.org/keywords/exponential-smoothing","display_name":"Exponential smoothing","score":0.8920351266860962},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6590636372566223},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6500519514083862},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.611262321472168},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5857318639755249},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4476979672908783},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.4420072138309479},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4318673014640808},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4318595826625824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39227455854415894},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3219336271286011},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19228890538215637}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.945499062538147},{"id":"https://openalex.org/C133710760","wikidata":"https://www.wikidata.org/wiki/Q775837","display_name":"Exponential smoothing","level":2,"score":0.8920351266860962},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6590636372566223},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6500519514083862},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.611262321472168},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5857318639755249},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4476979672908783},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.4420072138309479},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4318673014640808},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4318595826625824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39227455854415894},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3219336271286011},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19228890538215637},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1057/palgrave.jors.2602073","is_oa":false,"landing_page_url":"https://doi.org/10.1057/palgrave.jors.2602073","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:RePEc:pal:jorsoc:v:57:y:2006:i:9:d:10.1057_palgrave.jors.2602073","is_oa":false,"landing_page_url":"http://link.springer.com/10.1057/palgrave.jors.2602073","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1536917906","https://openalex.org/W1663792126","https://openalex.org/W1978516865","https://openalex.org/W1998491684","https://openalex.org/W2038697332","https://openalex.org/W2048665112","https://openalex.org/W2079065492","https://openalex.org/W2096590196","https://openalex.org/W2109083778","https://openalex.org/W2154326182","https://openalex.org/W2313953460","https://openalex.org/W2489822048","https://openalex.org/W2798058877","https://openalex.org/W2884206600","https://openalex.org/W3023786531","https://openalex.org/W3123887400","https://openalex.org/W4229539396","https://openalex.org/W4376051614"],"related_works":["https://openalex.org/W2091996104","https://openalex.org/W2584234271","https://openalex.org/W2365520989","https://openalex.org/W626441390","https://openalex.org/W2383431414","https://openalex.org/W4312690338","https://openalex.org/W2909877301","https://openalex.org/W2782187199","https://openalex.org/W4235728994","https://openalex.org/W2906471315"],"abstract_inverted_index":{"The":[0,117],"importance":[1],"of":[2,6,12,80,84,92,136],"predicting":[3],"future":[4],"values":[5],"a":[7,10,78],"time-series":[8,17,85,96],"transcends":[9],"range":[11],"disciplines.":[13],"Economic":[14],"and":[15,25,39,53,113,129],"business":[16],"are":[18],"typically":[19],"characterized":[20],"by":[21,37],"trend,":[22],"cycle,":[23],"seasonal,":[24],"random":[26],"components.":[27],"Powerful":[28],"methods":[29,44,128],"have":[30],"been":[31],"developed":[32],"to":[33],"capture":[34],"these":[35],"components":[36],"specifying":[38],"estimating":[40],"statistical":[41],"models.":[42,58],"These":[43],"include":[45],"exponential":[46],"smoothing,":[47],"autoregressive":[48],"integrated":[49],"moving":[50],"average":[51],"(ARIMA),":[52],"partially":[54,110],"adaptive":[55,111],"estimated":[56],"ARIMA":[57,101,107],"New":[59],"research":[60],"in":[61,134],"pattern":[62],"recognition":[63],"through":[64,109],"machine":[65],"learning":[66],"offers":[67],"innovative":[68],"methodologies":[69],"that":[70,120],"can":[71],"improve":[72],"forecasting":[73],"performance.":[74],"This":[75],"paper":[76],"presents":[77],"study":[79],"the":[81,126,131],"comparative":[82],"results":[83,118,133],"analysis":[86],"on":[87],"nine":[88,137],"problem":[89],"domains,":[90],"each":[91],"which":[93],"exhibits":[94],"differing":[95],"characteristics.":[97],"Comparative":[98],"analyses":[99],"use":[100],"selection":[102],"employing":[103],"an":[104],"intelligent":[105],"agent,":[106],"estimation":[108],"methods,":[112],"support":[114,121],"vector":[115,122],"machines.":[116],"find":[119],"machines":[123],"weakly":[124],"dominate":[125],"other":[127],"achieve":[130],"best":[132],"eight":[135],"different":[138],"data":[139],"sets.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
