{"id":"https://openalex.org/W7166292044","doi":"https://doi.org/10.1016/j.knosys.2026.116530","title":"Adaptive drift aware continual learning with pool-based model reuse for time series applications","display_name":"Adaptive drift aware continual learning with pool-based model reuse for time series applications","publication_year":2026,"publication_date":"2026-06-27","ids":{"openalex":"https://openalex.org/W7166292044","doi":"https://doi.org/10.1016/j.knosys.2026.116530"},"language":"en","primary_location":{"id":"doi:10.1016/j.knosys.2026.116530","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.knosys.2026.116530","pdf_url":null,"source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.knosys.2026.116530","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104318906","display_name":"Danlei Li","orcid":"https://orcid.org/0009-0007-6578-2241"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Danlei Li","raw_affiliation_strings":["Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand"],"raw_orcid":"https://orcid.org/0009-0007-6578-2241","affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007888592","display_name":"Mingyu Fan","orcid":"https://orcid.org/0000-0002-0492-4708"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Mingyu Fan","raw_affiliation_strings":["Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand"],"raw_orcid":"https://orcid.org/0009-0008-2991-0151","affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068740589","display_name":"Nirmal\u2010Kumar C. Nair","orcid":"https://orcid.org/0000-0002-8456-3999"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Nirmal-Kumar C Nair","raw_affiliation_strings":["Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand"],"raw_orcid":"https://orcid.org/0000-0002-8456-3999","affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091532881","display_name":"Kevin I\u2010Kai Wang","orcid":"https://orcid.org/0000-0001-8450-2558"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Kevin I-Kai Wang","raw_affiliation_strings":["Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand"],"raw_orcid":"https://orcid.org/0000-0001-8450-2558","affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Software Engineering, The University of Auckland, 20 Symonds Street, Auckland CBD, Auckland, 1010, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5091532881","https://openalex.org/A5104318906"],"corresponding_institution_ids":["https://openalex.org/I154130895"],"apc_list":{"value":3130,"currency":"USD","value_usd":3130},"apc_paid":{"value":3130,"currency":"USD","value_usd":3130},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.83201321,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"350","issue":null,"first_page":"116530","last_page":"116530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.8292999863624573,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.8292999863624573,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.07779999822378159,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.00559999980032444,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5252000093460083},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.4936000108718872},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4092000126838684},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.32339999079704285},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.298799991607666},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.28999999165534973}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6344000101089478},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5252000093460083},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.4936000108718872},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4092000126838684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3630000054836273},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.32339999079704285},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.29440000653266907},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.knosys.2026.116530","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.knosys.2026.116530","pdf_url":null,"source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.knosys.2026.116530","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.knosys.2026.116530","pdf_url":null,"source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1242748811","https://openalex.org/W2244109919","https://openalex.org/W2620661538","https://openalex.org/W2785362611","https://openalex.org/W2899638272","https://openalex.org/W2948517885","https://openalex.org/W2950361482","https://openalex.org/W2963166639","https://openalex.org/W3001100660","https://openalex.org/W3017897307","https://openalex.org/W3108350378","https://openalex.org/W3135908355","https://openalex.org/W3169667233","https://openalex.org/W4220851938","https://openalex.org/W4224316504","https://openalex.org/W4280549649","https://openalex.org/W4282813397","https://openalex.org/W4288057688","https://openalex.org/W4310699669","https://openalex.org/W4323314880","https://openalex.org/W4383550974","https://openalex.org/W4385337232","https://openalex.org/W4391093036","https://openalex.org/W4392453402","https://openalex.org/W4401344371","https://openalex.org/W4402955991","https://openalex.org/W4404147561","https://openalex.org/W4411211396","https://openalex.org/W4412721961","https://openalex.org/W4414414213","https://openalex.org/W7134187941"],"related_works":[],"abstract_inverted_index":{"Unsupervised":[0],"anomaly":[1,84],"detection":[2,26,85,147],"in":[3,86,179],"streaming":[4],"time":[5],"series":[6],"is":[7],"challenging":[8,182],"due":[9],"to":[10,49,51,58,175],"evolving":[11],"data":[12,88],"distributions":[13],"and":[14,55,79,101,118,122,145],"the":[15,186],"lack":[16],"of":[17,152],"labeled":[18],"anomalies,":[19],"where":[20],"concept":[21,120],"drift":[22,93,121,171,196],"can":[23,46,142],"significantly":[24],"degrade":[25],"accuracy":[27],"during":[28],"long-term":[29,192],"operation.":[30],"Most":[31],"existing":[32],"adaptive":[33,83],"methods":[34],"rely":[35],"on":[36,136,181],"uniform":[37],"update":[38],"strategies":[39,125],"or":[40,131],"continuous":[41],"incremental":[42],"learning.":[43],"Such":[44],"designs":[45],"be":[47],"slow":[48],"react":[50],"abrupt":[52],"distribution":[53],"shifts":[54],"are":[56],"prone":[57],"overwriting":[59],"previously":[60],"learned":[61],"regimes":[62],"when":[63],"patterns":[64],"recur.":[65],"This":[66],"paper":[67],"proposes":[68],"ADAPTS":[69,90,141,158],"(Adaptive":[70],"Drift-Aware":[71],"Pool-based":[72],"framework":[73,81,114],"for":[74,82,106],"Time":[75],"Series),":[76],"an":[77],"unsupervised":[78],"drift-aware":[80],"non-stationary":[87],"streams.":[89],"integrates":[91],"statistical":[92],"detection,":[94],"explicit":[95],"drift-type":[96],"classification,":[97],"drift-specific":[98],"model":[99,104,133],"adaptation,":[100],"a":[102,110],"bounded":[103],"pool":[105],"knowledge":[107],"reuse":[108],"within":[109],"unified":[111],"system.":[112],"The":[113],"distinguishes":[115],"sudden,":[116],"incremental,":[117],"recurrent":[119],"aligns":[123],"adaptation":[124],"accordingly":[126],"through":[127],"retraining,":[128],"controlled":[129],"fine-tuning,":[130],"selective":[132],"reuse.":[134],"Experiments":[135],"benchmark":[137],"datasets":[138],"show":[139,156],"that":[140,157],"keep":[143],"stable":[144],"reliable":[146],"results":[148,155],"under":[149,169,194],"different":[150],"types":[151],"drift.":[153],"Experimental":[154],"achieves":[159],"competitive":[160],"performance":[161,166],"across":[162],"multiple":[163],"datasets,":[164],"with":[165],"improvements":[167],"observed":[168],"several":[170],"scenarios,":[172],"including":[173],"up":[174],"0.11":[176],"absolute":[177],"gain":[178],"AUC":[180],"scenarios":[183],"such":[184],"as":[185],"NAB":[187],"dataset,":[188],"while":[189],"maintaining":[190],"improved":[191],"stability":[193],"diverse":[195],"conditions.":[197]},"counts_by_year":[],"updated_date":"2026-07-05T06:12:00.321722","created_date":"2026-06-28T00:00:00"}
