{"id":"https://openalex.org/W4387068308","doi":"https://doi.org/10.1109/tii.2023.3299611","title":"A Novel CVAE-Based Sequential Monte Carlo Framework for Dynamic Soft Sensor Applications","display_name":"A Novel CVAE-Based Sequential Monte Carlo Framework for Dynamic Soft Sensor Applications","publication_year":2023,"publication_date":"2023-09-26","ids":{"openalex":"https://openalex.org/W4387068308","doi":"https://doi.org/10.1109/tii.2023.3299611"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2023.3299611","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2023.3299611","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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":"https://openalex.org/A5009416402","display_name":"Wenxin Sun","orcid":"https://orcid.org/0000-0001-8052-4960"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Sun","raw_affiliation_strings":["School of the Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0001-8052-4960","affiliations":[{"raw_affiliation_string":"School of the Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032634509","display_name":"Weili Xiong","orcid":"https://orcid.org/0000-0002-9427-8809"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weili Xiong","raw_affiliation_strings":["School of the Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0002-9427-8809","affiliations":[{"raw_affiliation_string":"School of the Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019419996","display_name":"Hongtian Chen","orcid":"https://orcid.org/0000-0002-8600-9668"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtian Chen","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8600-9668","affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017597087","display_name":"Ranjith Chiplunkar","orcid":"https://orcid.org/0000-0001-5546-0918"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ranjith Chiplunkar","raw_affiliation_strings":["Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0001-5546-0918","affiliations":[{"raw_affiliation_string":"Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100432851","display_name":"Biao Huang","orcid":"https://orcid.org/0000-0001-9082-2216"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Biao Huang","raw_affiliation_strings":["Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0001-9082-2216","affiliations":[{"raw_affiliation_string":"Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1078,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.9196764,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"20","issue":"3","first_page":"3789","last_page":"3800"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9976000189781189,"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":0.9976000189781189,"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/T10791","display_name":"Advanced Control Systems Optimization","score":0.9829999804496765,"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/T11236","display_name":"Control Systems and Identification","score":0.9761999845504761,"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/computer-science","display_name":"Computer science","score":0.6365389227867126},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5712521076202393},{"id":"https://openalex.org/keywords/soft-sensor","display_name":"Soft sensor","score":0.5450504422187805},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5031158328056335},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.48808038234710693},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4274616241455078},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40446633100509644},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37502336502075195},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30823785066604614},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19738706946372986},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15423175692558289}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6365389227867126},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5712521076202393},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.5450504422187805},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5031158328056335},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.48808038234710693},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4274616241455078},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40446633100509644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37502336502075195},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30823785066604614},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19738706946372986},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15423175692558289},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.0},{"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2023.3299611","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2023.3299611","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G3396620864","display_name":null,"funder_award_id":"61773182","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4116981152","display_name":null,"funder_award_id":"202106790029","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1649946951","https://openalex.org/W1992281441","https://openalex.org/W2031815363","https://openalex.org/W2065636071","https://openalex.org/W2085862958","https://openalex.org/W2099717599","https://openalex.org/W2105722058","https://openalex.org/W2160337655","https://openalex.org/W2332443565","https://openalex.org/W2374834613","https://openalex.org/W2920714358","https://openalex.org/W2984637522","https://openalex.org/W2988720209","https://openalex.org/W3004005358","https://openalex.org/W3015966228","https://openalex.org/W3035753075","https://openalex.org/W3048582611","https://openalex.org/W3049769422","https://openalex.org/W3118694186","https://openalex.org/W3120987150","https://openalex.org/W3135396474","https://openalex.org/W3156231038","https://openalex.org/W3166723429","https://openalex.org/W3171438403","https://openalex.org/W3177704699","https://openalex.org/W4212888625","https://openalex.org/W4230472026","https://openalex.org/W4256619224","https://openalex.org/W4294982764","https://openalex.org/W4312916496","https://openalex.org/W4382568069","https://openalex.org/W6687045409"],"related_works":["https://openalex.org/W2374290272","https://openalex.org/W2097933059","https://openalex.org/W4386158748","https://openalex.org/W1970956258","https://openalex.org/W2408812858","https://openalex.org/W3127658115","https://openalex.org/W2742914308","https://openalex.org/W2330004501","https://openalex.org/W2017089693","https://openalex.org/W2703295919"],"abstract_inverted_index":{"In":[0,55,96],"industrial":[1],"processes,":[2],"quality":[3,123,184],"variables":[4,185],"are":[5,59,186,203],"typically":[6],"sampled":[7],"at":[8],"a":[9,83,119,179],"considerably":[10],"lower":[11,165],"frequency":[12],"than":[13],"system":[14,146],"inputs":[15],"due":[16],"to":[17,28,49,98,117,142,171,205],"technical":[18],"or":[19],"cost":[20],"constraints.":[21],"Dynamic":[22],"soft":[23,152,158],"sensors":[24],"utilize":[25],"temporal":[26],"prediction":[27,45,66,166,176],"bridge":[29],"these":[30,57,78],"sampling":[31],"gaps,":[32],"thus":[33],"enabling":[34],"real-time":[35],"closed-loop":[36,74],"control.":[37],"However,":[38],"existing":[39],"approaches":[40],"primarily":[41],"focus":[42],"on":[43,89,105,132],"one-step":[44],"accuracy,":[46],"potentially":[47],"leading":[48],"significant":[50],"deviations":[51],"in":[52],"long-term":[53],"predictions.":[54],"addition,":[56],"methods":[58],"incapable":[60],"of":[61,65,73,111,121,175,209],"evaluating":[62],"the":[63,70,90,107,112,115,133,135,161,169,173,189,197,207,210],"reliability":[64],"results,":[67],"subsequently":[68],"increasing":[69],"potential":[71,145],"risk":[72],"systems.":[75],"To":[76],"tackle":[77],"challenges,":[79],"this":[80,102,191],"study":[81],"presents":[82],"novel":[84],"regression":[85,100],"modeling":[86,106],"approach":[87],"based":[88],"conditional":[91],"variational":[92],"autoencoder":[93],"(CVAE)":[94],"framework.":[95],"contrast":[97],"traditional":[99,157],"approaches,":[101],"method":[103,138,163,192],"focuses":[104],"transition":[108],"probability":[109],"distribution":[110],"system,":[113],"allowing":[114],"model":[116],"produce":[118],"range":[120],"credible":[122],"variable":[124],"predictions":[125,195],"via":[126],"Monte":[127],"Carlo":[128],"(MC)":[129],"sampling.":[130],"Based":[131],"CVAEs,":[134],"sequential":[136],"MC":[137],"is":[139],"further":[140],"employed":[141],"simulate":[143],"diverse":[144],"state":[147],"trajectories,":[148],"thereby":[149],"achieving":[150],"multistep":[151],"measurement":[153,159],"prediction.":[154],"Compared":[155],"with":[156],"techniques,":[160],"proposed":[162,211],"demonstrates":[164],"biases":[167],"and":[168],"capacity":[170],"assess":[172],"credibility":[174],"results":[177],"from":[178],"probabilistic":[180],"standpoint.":[181],"When":[182],"online":[183],"assessed":[187],"by":[188],"laboratory,":[190],"can":[193],"update":[194],"utilizing":[196],"resampling":[198],"scheme.":[199,212],"Two":[200],"case":[201],"studies":[202],"offered":[204],"validate":[206],"effectiveness":[208]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}