{"id":"https://openalex.org/W3153369234","doi":"https://doi.org/10.1080/01969722.2021.1902049","title":"Aggregate Selection, Individual Selection, and Cluster Selection: An Empirical Evaluation and Implications for Systems Research","display_name":"Aggregate Selection, Individual Selection, and Cluster Selection: An Empirical Evaluation and Implications for Systems Research","publication_year":2021,"publication_date":"2021-06-14","ids":{"openalex":"https://openalex.org/W3153369234","doi":"https://doi.org/10.1080/01969722.2021.1902049","mag":"3153369234"},"language":"en","primary_location":{"id":"doi:10.1080/01969722.2021.1902049","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2021.1902049","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://durham-repository.worktribe.com/output/1245753","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069771812","display_name":"Dinesh Reddy Vangumalli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dinesh Reddy Vangumalli","raw_affiliation_strings":["Data Scientist, Resolution Life, USA"],"affiliations":[{"raw_affiliation_string":"Data Scientist, Resolution Life, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101989788","display_name":"\u039a\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03af\u03bd\u03bf\u03c2 \u039d\u03b9\u03ba\u03bf\u03bb\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2","orcid":"https://orcid.org/0000-0003-4268-2866"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Konstantinos Nikolopoulos","raw_affiliation_strings":["Durham University Business School, Durham, UK"],"affiliations":[{"raw_affiliation_string":"Durham University Business School, Durham, UK","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044153153","display_name":"Konstantia Litsiou","orcid":"https://orcid.org/0009-0009-6157-7683"},"institutions":[{"id":"https://openalex.org/I11983389","display_name":"Manchester Metropolitan University","ror":"https://ror.org/02hstj355","country_code":"GB","type":"education","lineage":["https://openalex.org/I11983389"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Konstantia Litsiou","raw_affiliation_strings":["Department of Marketing, Retail and Tourism, Manchester Metropolitan University Business School, Manchester, UK"],"affiliations":[{"raw_affiliation_string":"Department of Marketing, Retail and Tourism, Manchester Metropolitan University Business School, Manchester, UK","institution_ids":["https://openalex.org/I11983389"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101989788"],"corresponding_institution_ids":["https://openalex.org/I190082696"],"apc_list":null,"apc_paid":null,"fwci":0.1794,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51725079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"52","issue":"7","first_page":"553","last_page":"578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9966999888420105,"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":0.9966999888420105,"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":0.9918000102043152,"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/T14351","display_name":"Statistical and Computational Modeling","score":0.9847000241279602,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7839034795761108},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7156744003295898},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6881643533706665},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.62400221824646},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.6114827990531921},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5616412162780762},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.5252313613891602},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4807446002960205},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4629802107810974},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45484837889671326},{"id":"https://openalex.org/keywords/medoid","display_name":"Medoid","score":0.41649046540260315},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3759959638118744},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1641504168510437}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7839034795761108},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7156744003295898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6881643533706665},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.62400221824646},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.6114827990531921},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5616412162780762},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.5252313613891602},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4807446002960205},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4629802107810974},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45484837889671326},{"id":"https://openalex.org/C63085389","wikidata":"https://www.wikidata.org/wiki/Q4287912","display_name":"Medoid","level":3,"score":0.41649046540260315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3759959638118744},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1641504168510437},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1080/01969722.2021.1902049","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2021.1902049","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-article"},{"id":"pmh:oai:dro.dur.ac.uk.OAI2:32678","is_oa":false,"landing_page_url":"http://dro.dur.ac.uk/32678/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196258","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Cybernetics &amp; systems: an international journal, 2021, Vol.52(7), pp.553-578 [Peer Reviewed Journal]","raw_type":"Article"},{"id":"pmh:oai:e-space.mmu.ac.uk:627754","is_oa":false,"landing_page_url":"https://e-space.mmu.ac.uk/view/authors/099f9fc3ecf3a8d4b9070162b3498c78.html>","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:durham-repository.worktribe.com:1245753","is_oa":true,"landing_page_url":"https://durham-repository.worktribe.com/output/1245753","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:durham-repository.worktribe.com:1245753","is_oa":true,"landing_page_url":"https://durham-repository.worktribe.com/output/1245753","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W131856359","https://openalex.org/W156509570","https://openalex.org/W1499049447","https://openalex.org/W1594031697","https://openalex.org/W1944603233","https://openalex.org/W1963525398","https://openalex.org/W1996716987","https://openalex.org/W2016210396","https://openalex.org/W2036270743","https://openalex.org/W2043803919","https://openalex.org/W2044863747","https://openalex.org/W2048665112","https://openalex.org/W2053062040","https://openalex.org/W2055311466","https://openalex.org/W2056731984","https://openalex.org/W2069729888","https://openalex.org/W2077832579","https://openalex.org/W2085866051","https://openalex.org/W2089738378","https://openalex.org/W2098171900","https://openalex.org/W2117812871","https://openalex.org/W2119842880","https://openalex.org/W2121460124","https://openalex.org/W2133184712","https://openalex.org/W2134070777","https://openalex.org/W2154326182","https://openalex.org/W2161548576","https://openalex.org/W2171813245","https://openalex.org/W2179879290","https://openalex.org/W2313953460","https://openalex.org/W2911964244","https://openalex.org/W2963507686","https://openalex.org/W3122598275","https://openalex.org/W3125185139","https://openalex.org/W4212883601","https://openalex.org/W4237639624","https://openalex.org/W4244494905","https://openalex.org/W4294141750","https://openalex.org/W4298882835","https://openalex.org/W4302441299"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W2922073769","https://openalex.org/W4378510483","https://openalex.org/W2490526372","https://openalex.org/W2003394143","https://openalex.org/W4225271882","https://openalex.org/W2771206194"],"abstract_inverted_index":{"Data":[0],"analysts":[1],"when":[2],"forecasting":[3,22,34,88,137,158,193,203],"large":[4],"number":[5],"of":[6,13,119,169,176],"time":[7,38],"series,":[8],"they":[9],"regularly":[10],"employ":[11],"one":[12,175],"the":[14,25,32,46,51,57,69,81,115,120,131,135,144,165,170,190,197,201,207],"following":[15],"methodological":[16],"approaches:":[17],"either":[18],"select":[19,85],"a":[20,86,159],"single":[21,87],"method":[23,35,89],"for":[24,36,90,134,157,200],"entire":[26],"dataset":[27],"(aggregate":[28],"selection),":[29],"or":[30],"use":[31,174],"best":[33,132,191,198],"each":[37,91],"series":[39,118,168],"(individual":[40],"selection).":[41,94],"There":[42],"is":[43,53,74,112,162],"evidence":[44,125],"in":[45,60,114,164],"predictive":[47],"analytics":[48],"literature":[49],"that":[50,96],"former":[52],"more":[54],"robust":[55],"than":[56],"latter,":[58],"as":[59],"individual":[61],"selection":[62,142,153,156,205],"you":[63],"tend":[64],"to":[65,68,75,146,209],"overfit":[66],"models":[67],"data.":[70],"A":[71],"third":[72],"approach":[73],"first":[76,173],"identify":[77],"homogeneous":[78],"clusters":[79,133,199],"within":[80],"dataset,":[82],"and":[83,107,139,182],"then":[84,185],"cluster":[92,141,155,188],"(cluster":[93],"To":[95],"end,":[97],"we":[98],"examine":[99],"three":[100,177],"machine":[101],"learning":[102],"clustering":[103,178],"methods:":[104],"k-medoids,":[105,180],"k-NN":[106,181],"random":[108,128,183],"forests.":[109],"The":[110,123],"evaluation":[111,161],"performed":[113,163],"645":[116,166],"yearly":[117,167],"M3":[121,171],"competition.":[122],"empirical":[124],"suggests:":[126],"(a)":[127],"forests":[129,195],"provide":[130,196],"sequential":[136,202],"task,":[138],"(b)":[140],"has":[143,206],"potential":[145,208],"outperform":[147,210],"aggregate":[148,152,211],"selection.":[149,212],"HighlightsWe":[150],"compare":[151],"versus":[154],"datasetThe":[160],"competitionWe":[172],"terchiques:":[179],"forestsWe":[184],"forecast":[186],"every":[187],"with":[189],"possible":[192],"methodRandom":[194],"taskCluster":[204]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
