{"id":"https://openalex.org/W3040099731","doi":"https://doi.org/10.3390/s20133738","title":"LSTM-Based VAE-GAN for Time-Series Anomaly Detection","display_name":"LSTM-Based VAE-GAN for Time-Series Anomaly Detection","publication_year":2020,"publication_date":"2020-07-03","ids":{"openalex":"https://openalex.org/W3040099731","doi":"https://doi.org/10.3390/s20133738","mag":"3040099731","pmid":"https://pubmed.ncbi.nlm.nih.gov/32635374"},"language":"en","primary_location":{"id":"doi:10.3390/s20133738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20133738","pdf_url":"https://www.mdpi.com/1424-8220/20/13/3738/pdf?version=1594212262","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/13/3738/pdf?version=1594212262","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052170902","display_name":"Zijian Niu","orcid":"https://orcid.org/0009-0002-4301-0789"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijian Niu","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100719457","display_name":"Ke Yu","orcid":"https://orcid.org/0000-0002-1158-1483"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ke Yu","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051552380","display_name":"Xiaofei Wu","orcid":"https://orcid.org/0000-0002-4797-1256"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Wu","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100719457"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":12.3137,"has_fulltext":true,"cited_by_count":238,"citation_normalized_percentile":{"value":0.98900205,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"20","issue":"13","first_page":"3738","last_page":"3738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9944999814033508,"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/T14319","display_name":"Currency Recognition and Detection","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/discriminator","display_name":"Discriminator","score":0.965511679649353},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8918251991271973},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8821855187416077},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7196750044822693},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6285120248794556},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5950261354446411},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5945132970809937},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5420106649398804},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4940679371356964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47542479634284973},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44798544049263},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3550392985343933},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2458118498325348},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.2085389792919159},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.08279499411582947}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.965511679649353},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8918251991271973},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8821855187416077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7196750044822693},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6285120248794556},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5950261354446411},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5945132970809937},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5420106649398804},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4940679371356964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47542479634284973},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44798544049263},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3550392985343933},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2458118498325348},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2085389792919159},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.08279499411582947},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s20133738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20133738","pdf_url":"https://www.mdpi.com/1424-8220/20/13/3738/pdf?version=1594212262","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:32635374","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32635374","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:7374329","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7374329","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:67a0deb1ae324c548f0eaf9981c90799","is_oa":true,"landing_page_url":"https://doaj.org/article/67a0deb1ae324c548f0eaf9981c90799","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 13, p 3738 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/13/3738/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s20133738","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20133738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20133738","pdf_url":"https://www.mdpi.com/1424-8220/20/13/3738/pdf?version=1594212262","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G1474490597","display_name":null,"funder_award_id":"111 Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3418929802","display_name":null,"funder_award_id":"B08004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G731386166","display_name":null,"funder_award_id":"61601046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7422961271","display_name":"\u57fa\u4e8e\u590d\u6742\u7f51\u7edc\u7ed3\u6784\u548c\u76f8\u5173\u6027\u7684\u56e0\u7279\u7f51\u6d41\u91cf\u8bc6\u522b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61171098","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7470181681","display_name":null,"funder_award_id":"B08004","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3040099731.pdf","grobid_xml":"https://content.openalex.org/works/W3040099731.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W961884","https://openalex.org/W284754667","https://openalex.org/W1484442299","https://openalex.org/W1909320841","https://openalex.org/W1959608418","https://openalex.org/W2026493302","https://openalex.org/W2038194220","https://openalex.org/W2061122559","https://openalex.org/W2068835593","https://openalex.org/W2075698219","https://openalex.org/W2122646361","https://openalex.org/W2126831543","https://openalex.org/W2129249398","https://openalex.org/W2147620601","https://openalex.org/W2163557584","https://openalex.org/W2186910770","https://openalex.org/W2202109488","https://openalex.org/W2404243041","https://openalex.org/W2474046725","https://openalex.org/W2535642622","https://openalex.org/W2613310014","https://openalex.org/W2613328025","https://openalex.org/W2786088545","https://openalex.org/W2897825916","https://openalex.org/W2900906990","https://openalex.org/W2902455138","https://openalex.org/W2910068345","https://openalex.org/W2911200746","https://openalex.org/W2913556461","https://openalex.org/W2952042565","https://openalex.org/W2962736999","https://openalex.org/W2963166639","https://openalex.org/W2979898098","https://openalex.org/W3081229243","https://openalex.org/W3106543020","https://openalex.org/W3150435615","https://openalex.org/W3208688400","https://openalex.org/W4212770024","https://openalex.org/W6640963894","https://openalex.org/W7064111672"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3040099731","https://openalex.org/W2366944513","https://openalex.org/W3017266184","https://openalex.org/W4289406342","https://openalex.org/W2896600774","https://openalex.org/W2918377632","https://openalex.org/W3194885736","https://openalex.org/W3046391934","https://openalex.org/W4363671829"],"abstract_inverted_index":{"Time":[0],"series":[1,38,90],"anomaly":[2,39,59,91,146],"detection":[3,60,147],"is":[4],"widely":[5],"used":[6,135],"to":[7,45,53,110],"monitor":[8],"the":[9,13,17,24,47,54,58,96,103,105,108,114,118,121,125,137,139,142,145,163],"equipment":[10],"sates":[11],"through":[12],"data":[14],"collected":[15],"in":[16],"form":[18],"of":[19,113,117,124],"time":[20,37,89],"series.":[21],"At":[22,144],"present,":[23],"deep":[25],"learning":[26],"method":[27,43,87,100,165],"based":[28,152],"on":[29,153],"generative":[30],"adversarial":[31,83],"networks":[32,84,133],"(GAN)":[33],"has":[34],"emerged":[35],"for":[36,88],"detection.":[40],"However,":[41],"this":[42,72],"needs":[44],"find":[46],"best":[48],"mapping":[49,115],"from":[50],"real-time":[51],"space":[52,56],"latent":[55],"at":[57],"stage,":[61,148],"which":[62,93],"brings":[63],"new":[64],"errors":[65],"and":[66,107,120,141,156,168],"takes":[67],"a":[68,76],"long":[69,77,129],"time.":[70],"In":[71],"paper,":[73],"we":[74],"propose":[75],"short-term":[78,130],"memory-based":[79],"variational":[80],"autoencoder":[81],"generation":[82],"(LSTM-based":[85],"VAE-GAN)":[86],"detection,":[92],"effectively":[94],"solves":[95],"above":[97],"problems.":[98],"Our":[99],"jointly":[101],"trains":[102],"encoder,":[104,138],"generator":[106,140],"discriminator":[109,126],"take":[111],"advantage":[112],"ability":[116,123],"encoder":[119],"discrimination":[122,157],"simultaneously.":[127],"The":[128],"memory":[131],"(LSTM)":[132],"are":[134,150],"as":[136],"discriminator.":[143],"anomalies":[149],"detected":[151],"reconstruction":[154],"difference":[155],"results.":[158],"Experimental":[159],"results":[160],"show":[161],"that":[162],"proposed":[164],"can":[166],"quickly":[167],"accurately":[169],"detect":[170],"anomalies.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":28},{"year":2025,"cited_by_count":59},{"year":2024,"cited_by_count":59},{"year":2023,"cited_by_count":44},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":17}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}