{"id":"https://openalex.org/W7118169749","doi":"https://doi.org/10.1109/tkde.2025.3650739","title":"DLTTS: Diffusion Model for Long-Tailed Time Series Generation in Industrial Scenarios","display_name":"DLTTS: Diffusion Model for Long-Tailed Time Series Generation in Industrial Scenarios","publication_year":2026,"publication_date":"2026-01-05","ids":{"openalex":"https://openalex.org/W7118169749","doi":"https://doi.org/10.1109/tkde.2025.3650739"},"language":null,"primary_location":{"id":"doi:10.1109/tkde.2025.3650739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3650739","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","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/A5121974012","display_name":"Weijun Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weijun Hu","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399693","display_name":"Haifeng Zhang","orcid":"https://orcid.org/0000-0003-4206-7505"},"institutions":[{"id":"https://openalex.org/I4210113818","display_name":"China Electronic Product Reliability and Environmental Test Institute","ror":"https://ror.org/01f4k3b46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210113818"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Zhang","raw_affiliation_strings":["China Electronics Product Reliability and Environmental Test Institute, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"China Electronics Product Reliability and Environmental Test Institute, Guangzhou, China","institution_ids":["https://openalex.org/I4210113818"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693236","display_name":"Wenbin Chen","orcid":"https://orcid.org/0000-0001-8305-0764"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbin Chen","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087524440","display_name":"Kaihong Chen","orcid":"https://orcid.org/0009-0000-0321-1952"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaihong Chen","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103462538","display_name":"J. Y. Long","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhao Long","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121914104","display_name":"Wenli Shang","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenli Shang","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121913278","display_name":"Zhong Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Cao","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5121974012"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.02645959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"38","issue":"3","first_page":"1651","last_page":"1664"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.8353999853134155,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.8353999853134155,"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":0.015300000086426735,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.015300000086426735,"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/time-series","display_name":"Time series","score":0.6717000007629395},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6128000020980835},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4756999909877777},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4049000144004822},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3871999979019165},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.3837999999523163},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.35440000891685486},{"id":"https://openalex.org/keywords/industrial-production","display_name":"Industrial production","score":0.3458000123500824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7875999808311462},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6717000007629395},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6128000020980835},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4756999909877777},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4334999918937683},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4049000144004822},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.3837999999523163},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35440000891685486},{"id":"https://openalex.org/C82753439","wikidata":"https://www.wikidata.org/wiki/Q1419090","display_name":"Industrial production","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C68710425","wikidata":"https://www.wikidata.org/wiki/Q5275442","display_name":"Diffusion process","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2025.3650739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3650739","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5795854330062866,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2099454382","https://openalex.org/W2791694051","https://openalex.org/W3048236912","https://openalex.org/W3048988402","https://openalex.org/W3167297489","https://openalex.org/W4297364358","https://openalex.org/W4312901050","https://openalex.org/W4312933868","https://openalex.org/W4372342073","https://openalex.org/W4379382043","https://openalex.org/W4382203079","https://openalex.org/W4382775434","https://openalex.org/W4386320400","https://openalex.org/W4387010382","https://openalex.org/W4388282375","https://openalex.org/W4389610075","https://openalex.org/W4390343450","https://openalex.org/W4390872297","https://openalex.org/W4391468387","https://openalex.org/W4396757885","https://openalex.org/W4399392052","https://openalex.org/W4402120973","https://openalex.org/W4402916480","https://openalex.org/W4405179039","https://openalex.org/W4406731831","https://openalex.org/W4406826326"],"related_works":[],"abstract_inverted_index":{"Industrial":[0],"time":[1,21,75,88,121,126,152,166,172],"series":[2,22,76,89,127,153,167,173],"analysis":[3,34,48],"is":[4,104],"the":[5,16,31,109,114,139,148,160,187],"core":[6],"foundation":[7],"of":[8,20,33,58,150,164,191],"equipment":[9],"status":[10],"monitoring":[11],"and":[12,26,44,72,123,162,183],"industrial":[13,41,86],"intelligence.":[14],"However,":[15],"long-tailed":[17,87],"distribution":[18],"characteristics":[19],"caused":[23],"by":[24],"low-frequency":[25,144],"low-probability":[27],"events":[28],"seriously":[29],"restrict":[30],"performance":[32,52,180,189],"models.":[35],"In":[36],"key":[37],"scenarios":[38],"such":[39],"as":[40],"process":[42,117],"prediction":[43],"anomaly":[45],"detection,":[46],"data":[47,62],"models":[49],"face":[50],"obvious":[51],"bottlenecks":[53],"due":[54],"to":[55,106,118,137,142],"insufficient":[56],"representation":[57],"tail":[59,70,151,165],"events.":[60],"Existing":[61],"augmentation":[63],"methods":[64],"have":[65],"dual":[66],"limitations":[67],"in":[68,169,181],"capturing":[69],"patterns":[71,122],"modeling":[73],"long-distance":[74,120,125],"dependencies.":[77],"To":[78],"address":[79],"this":[80,82,192],"challenge,":[81],"paper":[83],"proposes":[84],"an":[85],"generator":[90],"(DLTTS)":[91],"model":[92,103],"based":[93],"on":[94],"a":[95,99],"diffusion":[96,116],"model.":[97],"Firstly,":[98],"hybrid":[100],"architecture":[101],"generation":[102,168,174],"constructed":[105],"deeply":[107],"integrate":[108],"encoder-decoder":[110],"informer":[111],"structure":[112],"with":[113],"traditional":[115],"maintain":[119],"achieve":[124],"output;":[128],"Secondly,":[129],"we":[130],"propose":[131],"Fourier-based":[132],"batch-Monte":[133],"Carlo":[134],"(FBMC)":[135],"loss":[136],"enhance":[138],"model's":[140],"ability":[141],"capture":[143],"events,":[145],"thereby":[146],"improve":[147],"quality":[149],"generation.":[154],"Experiments":[155],"show":[156],"that":[157],"DLTTS":[158],"maintains":[159],"authenticity":[161],"diversity":[163],"industrial-grade":[170],"long-tail":[171],"tasks.":[175],"It":[176],"also":[177],"exhibits":[178],"robust":[179],"imputation":[182],"forecasting":[184],"tasks,":[185],"verifying":[186],"multiple":[188],"advantages":[190],"method":[193],"for":[194],"cross-task":[195],"application.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2026-01-05T00:00:00"}