{"id":"https://openalex.org/W4389538721","doi":"https://doi.org/10.1109/tnnls.2023.3337876","title":"PAFormer: Anomaly Detection of Time Series With Parallel-Attention Transformer","display_name":"PAFormer: Anomaly Detection of Time Series With Parallel-Attention Transformer","publication_year":2023,"publication_date":"2023-12-11","ids":{"openalex":"https://openalex.org/W4389538721","doi":"https://doi.org/10.1109/tnnls.2023.3337876","pmid":"https://pubmed.ncbi.nlm.nih.gov/38079369"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3337876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3337876","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5040878857","display_name":"Ningning Bai","orcid":"https://orcid.org/0009-0009-0002-3230"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ningning Bai","raw_affiliation_strings":["Department of Mathematics, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029247516","display_name":"Xiaofeng Wang","orcid":"https://orcid.org/0000-0002-0861-8193"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaofeng Wang","raw_affiliation_strings":["Department of Mathematics, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076278720","display_name":"Ruidong Han","orcid":"https://orcid.org/0000-0002-4630-3731"},"institutions":[{"id":"https://openalex.org/I110262843","display_name":"Yuncheng University","ror":"https://ror.org/03qt1g669","country_code":"CN","type":"education","lineage":["https://openalex.org/I110262843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruidong Han","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","School of Mathematics and Information Technology, Yuncheng University, Yuncheng, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]},{"raw_affiliation_string":"School of Mathematics and Information Technology, Yuncheng University, Yuncheng, China","institution_ids":["https://openalex.org/I110262843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090570692","display_name":"Q. Wang","orcid":"https://orcid.org/0000-0001-6124-1586"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin Wang","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025763233","display_name":"Zinian Liu","orcid":"https://orcid.org/0000-0002-0369-0217"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zinian Liu","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5040878857"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.964,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.92992864,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"36","issue":"2","first_page":"3315","last_page":"3328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9945999979972839,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.7241470813751221},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6485311388969421},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5282798409461975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.506928026676178},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4760475158691406},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4416669011116028},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4110443890094757},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4090907573699951},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3805467188358307},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08928182721138}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7241470813751221},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6485311388969421},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5282798409461975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.506928026676178},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4760475158691406},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4416669011116028},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4110443890094757},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4090907573699951},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3805467188358307},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08928182721138},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3337876","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3337876","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38079369","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38079369","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G8252510314","display_name":null,"funder_award_id":"62376212","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1970088130","https://openalex.org/W2053125529","https://openalex.org/W2407991977","https://openalex.org/W2575694120","https://openalex.org/W2786827964","https://openalex.org/W2896605338","https://openalex.org/W2950361482","https://openalex.org/W2962736999","https://openalex.org/W2963166639","https://openalex.org/W2965433388","https://openalex.org/W3015316773","https://openalex.org/W3075060036","https://openalex.org/W3081497074","https://openalex.org/W3093787659","https://openalex.org/W3096831136","https://openalex.org/W3106543020","https://openalex.org/W3120093105","https://openalex.org/W3158264953","https://openalex.org/W3165446392","https://openalex.org/W3169450514","https://openalex.org/W3170937175","https://openalex.org/W3170981104","https://openalex.org/W3189124218","https://openalex.org/W3190748826","https://openalex.org/W3212158549","https://openalex.org/W4206503836","https://openalex.org/W4223531197","https://openalex.org/W4224315779","https://openalex.org/W4225512856","https://openalex.org/W4225680488","https://openalex.org/W4226182663","https://openalex.org/W4254182148","https://openalex.org/W4281388377","https://openalex.org/W4283318673","https://openalex.org/W4283696437","https://openalex.org/W4285600291","https://openalex.org/W4288046518","https://openalex.org/W4290943650","https://openalex.org/W4290948310","https://openalex.org/W4300003314","https://openalex.org/W4312881242","https://openalex.org/W4315783815","https://openalex.org/W4382239668","https://openalex.org/W4385245566","https://openalex.org/W4386075796","https://openalex.org/W4386076277","https://openalex.org/W6732332949","https://openalex.org/W6748102297","https://openalex.org/W6784869275","https://openalex.org/W6798224550","https://openalex.org/W6799025473","https://openalex.org/W6802061597","https://openalex.org/W6810225340"],"related_works":["https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W4294432981","https://openalex.org/W4321441197","https://openalex.org/W2953716828","https://openalex.org/W2469820710","https://openalex.org/W2750141660"],"abstract_inverted_index":{"Time-series":[0],"anomaly":[1,26],"detection":[2,27],"is":[3,75,189],"a":[4,13,79,100,154,192,234],"critical":[5],"task":[6],"with":[7,78,157,184],"significant":[8],"impact":[9],"as":[10,37],"it":[11],"serves":[12],"pivotal":[14],"role":[15],"in":[16,67],"the":[17,41,106,116,135,142,162,169,175,199,203,207,213,217,240],"field":[18],"of":[19,82,122,149,164,177,191,206],"data":[20,46,74,166,186,223],"mining":[21],"and":[22,48,119,141,153,252],"quality":[23],"management.":[24],"Current":[25],"methods":[28,39,54],"are":[29],"typically":[30],"based":[31],"on":[32,56,245],"reconstruction":[33],"or":[34],"forecasting":[35],"algorithms,":[36],"these":[38],"have":[40,181],"capability":[42],"to":[43,65,91,168,174,215,228,238],"learn":[44,216],"compressed":[45],"representations":[47],"model":[49,92],"time":[50,123],"dependencies.":[51],"However,":[52],"most":[53],"rely":[55],"learning":[57,93],"normal":[58],"distribution":[59],"patterns,":[60],"which":[61,88,110,130,225],"can":[62,89],"be":[63],"difficult":[64],"achieve":[66],"real-world":[68,72],"engineering":[69],"applications.":[70],"Furthermore,":[71],"time-series":[73],"highly":[76],"imbalanced,":[77],"severe":[80],"lack":[81],"representative":[83],"samples":[84],"for":[85,221],"anomalous":[86,178],"data,":[87],"lead":[90],"failure.":[94],"In":[95],"this":[96],"article,":[97],"we":[98,126,232],"propose":[99,233],"novel":[101],"end-to-end":[102],"unsupervised":[103],"framework":[104],"called":[105],"parallel-attention":[107,128],"transformer":[108],"(PAFormer),":[109],"discriminates":[111],"anomalies":[112],"by":[113],"modeling":[114],"both":[115],"global":[117,136],"characteristics":[118],"local":[120,143],"patterns":[121],"series.":[124],"Specifically,":[125],"construct":[127],"(PA),":[129],"includes":[131],"two":[132,150],"core":[133],"modules:":[134],"enhanced":[137],"representation":[138],"module":[139,145],"(GERM)":[140],"perception":[144],"(LPM).":[146],"GERM":[147],"consists":[148],"pattern":[151],"units":[152],"normalization":[155],"module,":[156],"attention":[158],"weights":[159],"that":[160,197,259],"indicate":[161],"relationship":[163],"each":[165,222],"point":[167],"whole":[170],"series":[171],"(global).":[172],"Due":[173],"rarity":[176],"points,":[179],"they":[180],"strong":[182],"associations":[183],"adjacent":[185],"points.":[187],"LPM":[188],"composed":[190],"learnable":[193],"Laplace":[194],"kernel":[195,208],"function":[196,209],"learns":[198],"neighborhood":[200],"relevancies":[201],"through":[202],"distributional":[204,219],"properties":[205],"(local).":[210],"We":[211,242],"employ":[212],"PA":[214],"global-local":[218],"differences":[220],"point,":[224],"enables":[226],"us":[227],"discriminate":[229],"anomalies.":[230],"Finally,":[231],"two-stage":[235],"adversarial":[236],"loss":[237],"optimize":[239],"model.":[241],"conduct":[243],"experiments":[244],"five":[246],"public":[247],"benchmark":[248],"datasets":[249],"(real-world":[250],"datasets)":[251],"one":[253],"synthetic":[254],"dataset.":[255],"The":[256],"results":[257],"show":[258],"PAFormer":[260],"outperforms":[261],"state-of-the-art":[262],"baselines.":[263]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
