{"id":"https://openalex.org/W7140220789","doi":"https://doi.org/10.1115/1.4071469","title":"Hybrid Temporal Modeling and Generative Augmentation for Imbalanced Multivariate Time Series Anomaly Detection in Engineering Systems","display_name":"Hybrid Temporal Modeling and Generative Augmentation for Imbalanced Multivariate Time Series Anomaly Detection in Engineering Systems","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140220789","doi":"https://doi.org/10.1115/1.4071469"},"language":"en","primary_location":{"id":"doi:10.1115/1.4071469","is_oa":false,"landing_page_url":"https://doi.org/10.1115/1.4071469","pdf_url":null,"source":{"id":"https://openalex.org/S173178594","display_name":"Journal of Computing and Information Science in Engineering","issn_l":"1530-9827","issn":["1530-9827","1944-7078"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316053","host_organization_name":"ASM International","host_organization_lineage":["https://openalex.org/P4310316053"],"host_organization_lineage_names":["ASM International"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing and Information Science in 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":null,"display_name":"Ahmed Shoyeb Raihan","orcid":null},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmed Shoyeb Raihan","raw_affiliation_strings":["West Virginia University Department of Industrial and Management Systems Engineering, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West Virginia University Department of Industrial and Management Systems Engineering, , ,","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Farzana Islam","orcid":null},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farzana Islam","raw_affiliation_strings":["West Virginia University Department of Industrial and Management Systems Engineering, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West Virginia University Department of Industrial and Management Systems Engineering, , ,","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhichao Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhichao Liu","raw_affiliation_strings":["West Virginia University Department of Industrial and Management Systems Engineering, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West Virginia University Department of Industrial and Management Systems Engineering, , ,","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Srinjoy Das","orcid":null},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinjoy Das","raw_affiliation_strings":["West Virginia University Department of Data Science, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West Virginia University Department of Data Science, , ,","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"last","author":{"id":null,"display_name":"Imtiaz Ahmed","orcid":null},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Imtiaz Ahmed","raw_affiliation_strings":["West Virginia University Department of Industrial and Management Systems Engineering, , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"West Virginia University Department of Industrial and Management Systems Engineering, , ,","institution_ids":["https://openalex.org/I12097938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I12097938"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31137403,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"7","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.49219998717308044,"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":0.49219998717308044,"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":0.40950000286102295,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.02850000001490116,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/anomaly-detection","display_name":"Anomaly detection","score":0.7315000295639038},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.620199978351593},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5645999908447266},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.49239999055862427},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.46369999647140503},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4375999867916107},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.40380001068115234},{"id":"https://openalex.org/keywords/generative-design","display_name":"Generative Design","score":0.3889999985694885}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7315000295639038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6966999769210815},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.620199978351593},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5645999908447266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5378999710083008},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.49239999055862427},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.46369999647140503},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4375999867916107},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43560001254081726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4255000054836273},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.40380001068115234},{"id":"https://openalex.org/C184408114","wikidata":"https://www.wikidata.org/wiki/Q1502022","display_name":"Generative Design","level":3,"score":0.3889999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3853999972343445},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.3817000091075897},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.37439998984336853},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.3398999869823456},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3018999993801117},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.28380000591278076}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1115/1.4071469","is_oa":false,"landing_page_url":"https://doi.org/10.1115/1.4071469","pdf_url":null,"source":{"id":"https://openalex.org/S173178594","display_name":"Journal of Computing and Information Science in Engineering","issn_l":"1530-9827","issn":["1530-9827","1944-7078"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316053","host_organization_name":"ASM International","host_organization_lineage":["https://openalex.org/P4310316053"],"host_organization_lineage_names":["ASM International"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing and Information Science in Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5620973110198975,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":97,"referenced_works":["https://openalex.org/W2090527041","https://openalex.org/W2093859880","https://openalex.org/W2117672932","https://openalex.org/W2175657233","https://openalex.org/W2437112748","https://openalex.org/W2460856114","https://openalex.org/W2501244995","https://openalex.org/W2736435690","https://openalex.org/W2738336658","https://openalex.org/W2763099889","https://openalex.org/W2800788706","https://openalex.org/W2889165715","https://openalex.org/W2906498146","https://openalex.org/W2944052783","https://openalex.org/W2946084162","https://openalex.org/W2963214893","https://openalex.org/W2966153025","https://openalex.org/W2975396892","https://openalex.org/W2978834409","https://openalex.org/W2979625610","https://openalex.org/W2987793235","https://openalex.org/W2989219518","https://openalex.org/W2995015263","https://openalex.org/W3003160776","https://openalex.org/W3004207920","https://openalex.org/W3012450219","https://openalex.org/W3022375718","https://openalex.org/W3034294191","https://openalex.org/W3039222472","https://openalex.org/W3046296398","https://openalex.org/W3091068909","https://openalex.org/W3108350378","https://openalex.org/W3117098906","https://openalex.org/W3133618741","https://openalex.org/W3133978444","https://openalex.org/W3134537993","https://openalex.org/W3140570329","https://openalex.org/W3157152805","https://openalex.org/W3160936371","https://openalex.org/W3164952570","https://openalex.org/W3168992578","https://openalex.org/W3170578864","https://openalex.org/W3175950569","https://openalex.org/W3181655313","https://openalex.org/W3184365971","https://openalex.org/W3185247140","https://openalex.org/W3186020689","https://openalex.org/W3186512740","https://openalex.org/W3192648431","https://openalex.org/W3195279647","https://openalex.org/W3196524163","https://openalex.org/W3198381997","https://openalex.org/W3202601107","https://openalex.org/W4225526013","https://openalex.org/W4226076258","https://openalex.org/W4281703655","https://openalex.org/W4281929036","https://openalex.org/W4288057688","https://openalex.org/W4288420507","https://openalex.org/W4306645406","https://openalex.org/W4306836273","https://openalex.org/W4308149818","https://openalex.org/W4308482467","https://openalex.org/W4310721640","https://openalex.org/W4313644197","https://openalex.org/W4317790219","https://openalex.org/W4323314880","https://openalex.org/W4327568850","https://openalex.org/W4362678565","https://openalex.org/W4380742472","https://openalex.org/W4380986428","https://openalex.org/W4382403051","https://openalex.org/W4385397411","https://openalex.org/W4385695948","https://openalex.org/W4387675736","https://openalex.org/W4387695057","https://openalex.org/W4387745459","https://openalex.org/W4388419478","https://openalex.org/W4389450167","https://openalex.org/W4389922975","https://openalex.org/W4392309171","https://openalex.org/W4392365138","https://openalex.org/W4396626043","https://openalex.org/W4396951866","https://openalex.org/W4399457657","https://openalex.org/W4400647693","https://openalex.org/W4401726558","https://openalex.org/W4402056503","https://openalex.org/W4403441422","https://openalex.org/W4404238271","https://openalex.org/W4407151755","https://openalex.org/W4409045576","https://openalex.org/W4409152758","https://openalex.org/W4409989669","https://openalex.org/W4411794411","https://openalex.org/W4412030696","https://openalex.org/W4413913950"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Multivariate":[1],"time":[2],"series":[3],"(MTS)":[4],"data":[5],"are":[6,38],"central":[7],"to":[8,138],"engineering":[9,227],"systems,":[10],"where":[11,229],"streams":[12],"of":[13,24,193],"sensor":[14],"signals":[15],"enable":[16],"trend":[17],"analysis,":[18],"anomaly":[19,106],"detection,":[20],"and":[21,29,42,58,86,147,154,180],"the":[22,61,113,118,171,175,204],"discovery":[23],"operating":[25],"patterns\u2014supporting":[26],"predictive":[27],"maintenance":[28],"quality":[30],"control.":[31],"Yet,":[32],"analyzing":[33],"MTS":[34,105],"remains":[35,112],"challenging:":[36],"faults":[37],"rare,":[39],"severely":[40],"imbalanced,":[41],"embedded":[43],"in":[44,178,226],"long":[45],"contexts":[46],"with":[47,120,170,189,219],"overlapping":[48],"modes.":[49],"These":[50],"challenges":[51],"demand":[52],"models":[53],"that":[54,185],"capture":[55],"extended":[56],"dependencies":[57],"focus":[59],"on":[60,144,161],"most":[62],"informative":[63],"intervals.":[64],"To":[65],"address":[66],"this,":[67],"we":[68,116],"design":[69],"a":[70,102,121,131,190,200],"hybrid":[71],"deep":[72],"learning":[73],"architecture":[74],"integrating":[75],"recurrent":[76,97],"units":[77],"for":[78,83,89,206],"long-horizon":[79],"dynamics,":[80],"attention":[81],"layers":[82],"critical":[84],"time-steps,":[85],"temporal":[87,152,216],"convolutions":[88],"multiscale":[90],"local":[91,145],"patterns.":[92],"We":[93,157,182],"propose":[94],"GAT-Net":[95],"(gated":[96],"unit":[98],"(GRU)-attention-temporal":[99],"convolutional":[100],"network),":[101],"robust":[103],"end-to-end":[104],"detector.":[107],"Because":[108],"severe":[109],"class":[110],"imbalance":[111],"dominant":[114],"barrier,":[115],"extend":[117],"backbone":[119],"generative":[122,134,172,220],"augmentation":[123,221],"strategy,":[124],"developing":[125],"DA-GAT-Net":[126],"(data-augmented":[127],"GAT-Net).":[128],"It":[129],"uses":[130],"segment-aware":[132],"conditional":[133],"adversarial":[135],"network":[136],"(GAN)":[137],"synthesize":[139],"rare":[140],"fault":[141,224],"segments":[142],"conditioned":[143],"context":[146],"inserts":[148],"them":[149],"chronologically,":[150],"preserving":[151],"continuity":[153],"cross-sensor":[155],"correlations.":[156],"evaluate":[158],"our":[159],"frameworks":[160],"an":[162],"industrial":[163],"benchmark":[164],"dataset.":[165],"They":[166],"outperform":[167],"state-of-the-art":[168],"baselines,":[169],"extension":[173],"yielding":[174],"largest":[176],"gains":[177],"recall":[179],"F1-score.":[181],"also":[183],"show":[184],"sensitivity":[186],"rises":[187],"sharply":[188],"moderate":[191],"amount":[192],"synthetic":[194],"anomalies":[195,231],"but":[196],"levels":[197],"off":[198],"beyond":[199],"balanced":[201],"ratio,":[202],"underscoring":[203],"need":[205],"controlled,":[207],"structure-preserving":[208],"generation.":[209],"Overall,":[210],"this":[211],"study":[212],"highlights":[213],"how":[214],"attention-guided":[215],"modeling":[217],"combined":[218],"can":[222],"enhance":[223],"detection":[225],"systems":[228],"missed":[230],"carry":[232],"high":[233],"operational":[234],"costs.":[235]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-03-25T00:00:00"}