{"id":"https://openalex.org/W3183908579","doi":"https://doi.org/10.1109/tnnls.2021.3086323","title":"Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring","display_name":"Deep Neural Network-Embedded Stochastic Nonlinear State-Space Models and Their Applications to Process Monitoring","publication_year":2021,"publication_date":"2021-07-26","ids":{"openalex":"https://openalex.org/W3183908579","doi":"https://doi.org/10.1109/tnnls.2021.3086323","mag":"3183908579","pmid":"https://pubmed.ncbi.nlm.nih.gov/34310323"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3086323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3086323","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/A5101563350","display_name":"Kai Wang","orcid":"https://orcid.org/0000-0003-1396-9825"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Wang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-1396-9825","affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045957489","display_name":"Junghui Chen","orcid":"https://orcid.org/0000-0002-9994-839X"},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Junghui Chen","raw_affiliation_strings":["Department of Chemical Engineering, Chung-Yuan Christian University, Taoyuan City, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-9994-839X","affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, Chung-Yuan Christian University, Taoyuan City, Taiwan","institution_ids":["https://openalex.org/I151221077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048733958","display_name":"Zhihuan Song","orcid":"https://orcid.org/0000-0003-4098-6479"},"institutions":[{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihuan Song","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4098-6479","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740826","display_name":"Yalin Wang","orcid":"https://orcid.org/0000-0002-1876-7707"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalin Wang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-1876-7707","affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101971818","display_name":"Chunhua Yang","orcid":"https://orcid.org/0000-0002-3770-9887"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhua Yang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-3770-9887","affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6938,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.93713958,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"33","issue":"12","first_page":"7682","last_page":"7694"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":1.0,"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":1.0,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9846000075340271,"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/computer-science","display_name":"Computer science","score":0.6823616623878479},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6377640962600708},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5663127303123474},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5542591214179993},{"id":"https://openalex.org/keywords/process-state","display_name":"Process state","score":0.5376334190368652},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5238156914710999},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5126734972000122},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4957081079483032},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.4622141718864441},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4260806739330292},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4108428657054901},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.3430047035217285},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33914074301719666},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16345548629760742}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6823616623878479},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6377640962600708},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5663127303123474},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5542591214179993},{"id":"https://openalex.org/C183560197","wikidata":"https://www.wikidata.org/wiki/Q7247302","display_name":"Process state","level":3,"score":0.5376334190368652},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5238156914710999},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5126734972000122},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4957081079483032},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.4622141718864441},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4260806739330292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4108428657054901},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3430047035217285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33914074301719666},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16345548629760742},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017711","descriptor_name":"Nonlinear Dynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017711","descriptor_name":"Nonlinear Dynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017711","descriptor_name":"Nonlinear Dynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018561","descriptor_name":"Space Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018561","descriptor_name":"Space Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018561","descriptor_name":"Space Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3086323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3086323","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:34310323","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34310323","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G3167315294","display_name":null,"funder_award_id":"U1911401","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G38666687","display_name":null,"funder_award_id":"62003373","funder_id":"https://openalex.org/F4320331088","funder_display_name":"Natural Science Foundation for Young Scientists of Shanxi Province"},{"id":"https://openalex.org/G5217592482","display_name":"Development of Novel Variational Autoencoders for Batch Process Monitoring: Unsupervised/Semi-Supervised, Multi-Modes/Dynamic, Data/Model Transfer Learning","funder_award_id":"MOST109-2221-E033-013-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G5996937881","display_name":null,"funder_award_id":"62003373","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"},{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320331088","display_name":"Natural Science Foundation for Young Scientists of Shanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W4952878","https://openalex.org/W567350711","https://openalex.org/W1419302472","https://openalex.org/W1933340426","https://openalex.org/W1966296768","https://openalex.org/W1966863755","https://openalex.org/W2003967703","https://openalex.org/W2014241185","https://openalex.org/W2025735965","https://openalex.org/W2072080277","https://openalex.org/W2120135212","https://openalex.org/W2140327685","https://openalex.org/W2169347809","https://openalex.org/W2199150779","https://openalex.org/W2296771229","https://openalex.org/W2342028629","https://openalex.org/W2417218580","https://openalex.org/W2467604901","https://openalex.org/W2473060649","https://openalex.org/W2563202971","https://openalex.org/W2585287312","https://openalex.org/W2607253354","https://openalex.org/W2607899278","https://openalex.org/W2731450000","https://openalex.org/W2764120290","https://openalex.org/W2794223277","https://openalex.org/W2794239758","https://openalex.org/W2803804323","https://openalex.org/W2888588474","https://openalex.org/W2903722520","https://openalex.org/W2912345712","https://openalex.org/W2945532623","https://openalex.org/W2963779771","https://openalex.org/W2984361892","https://openalex.org/W2995696070","https://openalex.org/W3018109943","https://openalex.org/W3035805403","https://openalex.org/W3111796587","https://openalex.org/W4212863985","https://openalex.org/W6640284076","https://openalex.org/W6685152286","https://openalex.org/W6720208624","https://openalex.org/W6751556005","https://openalex.org/W6772235576","https://openalex.org/W6776238290"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W4225394202","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W1847088711","https://openalex.org/W2810107741"],"abstract_inverted_index":{"Process":[0],"complexities":[1],"are":[2,103,144],"characterized":[3],"by":[4,117,205],"strong":[5],"nonlinearities,":[6,165],"dynamics,":[7,167],"and":[8,40,70,81,99,121,138,168,186],"uncertainties.":[9],"Monitoring":[10],"such":[11,182],"a":[12,16,47,60,67,71],"complex":[13,164],"process":[14,86,94,101,122,154,158,166,169],"requires":[15],"high-quality":[17],"model":[18,27,102,150,160],"describing":[19],"the":[20,37,63,78,82,100,112,118,129,136,139,148,153,179,194,197,201,211,217],"corresponding":[21],"nonlinear":[22,49],"dynamic":[23],"behavior.":[24],"The":[25,96,156],"proposed":[26,75,157,198],"is":[28,74,115,132],"constructed":[29],"using":[30,210],"deep":[31],"neural":[32,56],"networks":[33],"(DNNs)":[34],"to":[35,76,124],"represent":[36],"state":[38,131],"transition":[39],"observation":[41],"generation,":[42],"both":[43],"of":[44,62,85,172,196],"which":[45,88,173],"constitute":[46],"stochastic":[48],"state-space":[50],"model.":[51],"A":[52],"new":[53],"bidirectional":[54],"recurrent":[55],"network":[57],"(RNN),":[58],"creating":[59],"connection":[61],"hidden":[64],"layer":[65],"between":[66],"forward":[68],"RNN":[69],"backward":[72],"RNN,":[73],"generate":[77,90],"filtering":[79,113],"estimation":[80,84],"smoothing":[83,97],"states":[87],"further":[89],"observations":[91],"with":[92,107,163],"DNN-based":[93],"models.":[95],"estimator":[98,114],"first":[104],"learned":[105,119,149],"offline":[106],"all":[108,171],"collected":[109],"samples.":[110],"Then":[111],"fine-tuned":[116],"smoother":[120],"models":[123],"achieve":[125],"real-time":[126],"monitoring":[127,152,159],"since":[128],"filter":[130],"estimated":[133],"based":[134,146],"on":[135,147],"past":[137],"current":[140],"observations.":[141],"Two":[142,189],"indices":[143],"designed":[145],"for":[151,178],"anomaly.":[155],"can":[161,174],"deal":[162],"uncertainties,":[170],"be":[175],"very":[176],"challenging":[177],"existing":[180],"methods,":[181],"as":[183],"kernel":[184],"mapping":[185],"stacked":[187],"auto-encoder.":[188],"case":[190],"studies":[191],"validate":[192],"that":[193],"effectiveness":[195],"method":[199],"outperforms":[200],"other":[202],"comparative":[203],"methods":[204],"at":[206],"least":[207],"10%":[208],"when":[209],"averaged":[212],"fault":[213],"detection":[214],"rate":[215],"in":[216],"industrial":[218],"experimental":[219],"data.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}