{"id":"https://openalex.org/W4382936032","doi":"https://doi.org/10.23919/acc55779.2023.10156393","title":"Dynamic Probabilistic Latent Variable Model with Exogenous Variables for Dynamic Anomaly Detection","display_name":"Dynamic Probabilistic Latent Variable Model with Exogenous Variables for Dynamic Anomaly Detection","publication_year":2023,"publication_date":"2023-05-31","ids":{"openalex":"https://openalex.org/W4382936032","doi":"https://doi.org/10.23919/acc55779.2023.10156393"},"language":"en","primary_location":{"id":"doi:10.23919/acc55779.2023.10156393","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc55779.2023.10156393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 American Control Conference (ACC)","raw_type":"proceedings-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/A5036340946","display_name":"Bo Xu","orcid":"https://orcid.org/0000-0002-6443-6298"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Bo Xu","raw_affiliation_strings":["University of Waterloo,Department of Chemical Engineering,Waterloo,Canada,N2L 3G1"],"affiliations":[{"raw_affiliation_string":"University of Waterloo,Department of Chemical Engineering,Waterloo,Canada,N2L 3G1","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001958131","display_name":"Qinqin Zhu","orcid":"https://orcid.org/0000-0001-9258-0839"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Qinqin Zhu","raw_affiliation_strings":["University of Waterloo,Department of Chemical Engineering,Waterloo,Canada,N2L 3G1"],"affiliations":[{"raw_affiliation_string":"University of Waterloo,Department of Chemical Engineering,Waterloo,Canada,N2L 3G1","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036340946"],"corresponding_institution_ids":["https://openalex.org/I151746483"],"apc_list":null,"apc_paid":null,"fwci":0.1876,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44800592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3945","last_page":"3950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T14470","display_name":"Advanced Data Processing Techniques","score":0.9879999756813049,"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"}},{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.7755913734436035},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7092329263687134},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6909815669059753},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6407895088195801},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5750954151153564},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5483161807060242},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49686935544013977},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4585876166820526},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4453658163547516},{"id":"https://openalex.org/keywords/latent-variable-model","display_name":"Latent variable model","score":0.4345604181289673},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33811044692993164},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32998520135879517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22184467315673828},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.20777881145477295},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1824561059474945}],"concepts":[{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.7755913734436035},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7092329263687134},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6909815669059753},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407895088195801},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5750954151153564},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5483161807060242},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49686935544013977},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4585876166820526},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4453658163547516},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.4345604181289673},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33811044692993164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32998520135879517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22184467315673828},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.20777881145477295},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1824561059474945},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc55779.2023.10156393","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc55779.2023.10156393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1711410201","https://openalex.org/W1841820628","https://openalex.org/W1964940342","https://openalex.org/W1987036416","https://openalex.org/W2004186751","https://openalex.org/W2076818396","https://openalex.org/W2077791644","https://openalex.org/W2089468765","https://openalex.org/W2117621792","https://openalex.org/W2125027820","https://openalex.org/W2126111600","https://openalex.org/W2146610201","https://openalex.org/W2169347809","https://openalex.org/W2509008543","https://openalex.org/W2614622879","https://openalex.org/W2626923521","https://openalex.org/W2732259981","https://openalex.org/W2896690851","https://openalex.org/W2974638775","https://openalex.org/W3043554402","https://openalex.org/W3171633131","https://openalex.org/W4212863985","https://openalex.org/W4230556997"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2546021431","https://openalex.org/W2581127593","https://openalex.org/W2962930338","https://openalex.org/W4302439501","https://openalex.org/W2461917396","https://openalex.org/W2037497866","https://openalex.org/W4243467573","https://openalex.org/W62001224","https://openalex.org/W1502435251"],"abstract_inverted_index":{"A":[0],"novel":[1],"dynamic":[2,27,96,103],"probabilistic":[3],"latent":[4,34],"variable":[5],"model":[6,80],"with":[7,20],"exogenous":[8,72],"variables":[9,35,69],"(DPLVMX)":[10],"is":[11,63,75,90,99,109],"proposed":[12,45,100,117],"in":[13,38,43,55],"this":[14],"article":[15],"to":[16,48,65,101,111],"capture":[17],"system":[18],"dynamics":[19],"the":[21,44,50,56,71,79,113,116],"existence":[22],"of":[23,52,82,115],"random":[24],"noises.":[25],"The":[26,105],"auto-regressive":[28],"relations":[29,81],"between":[30],"current":[31],"and":[32],"past":[33],"are":[36],"extracted":[37],"a":[39,59,94],"Markov":[40],"state-space":[41],"form":[42],"model.":[46],"Furthermore,":[47],"strengthen":[49],"utilization":[51],"valuable":[53],"information":[54],"collected":[57],"data,":[58],"composite":[60],"loading":[61],"index":[62,98],"designed":[64],"select":[66],"some":[67],"interested":[68],"as":[70],"variables,":[73],"which":[74],"explicitly":[76],"incorporated":[77],"into":[78],"DPLVMX.":[83],"An":[84],"improved":[85],"DPLVM":[86],"based":[87],"monitoring":[88,97],"scheme":[89],"also":[91],"designed,":[92],"where":[93],"new":[95],"detect":[102],"anomalies.":[104],"Tennessee":[106],"Eastman":[107],"process":[108],"used":[110],"illustrate":[112],"superiority":[114],"algorithm.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
