{"id":"https://openalex.org/W3171398265","doi":"https://doi.org/10.1109/tnnls.2021.3085869","title":"A Deep Probabilistic Transfer Learning Framework for Soft Sensor Modeling With Missing Data","display_name":"A Deep Probabilistic Transfer Learning Framework for Soft Sensor Modeling With Missing Data","publication_year":2021,"publication_date":"2021-06-15","ids":{"openalex":"https://openalex.org/W3171398265","doi":"https://doi.org/10.1109/tnnls.2021.3085869","mag":"3171398265","pmid":"https://pubmed.ncbi.nlm.nih.gov/34129507"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3085869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3085869","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/A5081043925","display_name":"Zheng Chai","orcid":"https://orcid.org/0000-0001-9823-2990"},"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":"Zheng Chai","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/0000-0001-9823-2990","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/A5038929132","display_name":"Chunhui Zhao","orcid":"https://orcid.org/0000-0002-0254-5763"},"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":"Chunhui Zhao","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/0000-0002-0254-5763","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/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"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019419996","display_name":"Hongtian Chen","orcid":"https://orcid.org/0000-0002-8600-9668"},"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":"Hongtian Chen","raw_affiliation_strings":["Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0002-8600-9668","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":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.327,"has_fulltext":false,"cited_by_count":124,"citation_normalized_percentile":{"value":0.98815262,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"33","issue":"12","first_page":"7598","last_page":"7609"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9994999766349792,"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":0.9994999766349792,"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/T12676","display_name":"Machine Learning and ELM","score":0.9940000176429749,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9832000136375427,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/soft-sensor","display_name":"Soft sensor","score":0.7824256420135498},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6995914578437805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6246525049209595},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6186337471008301},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.591688871383667},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5903066992759705},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5779029726982117},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.5347935557365417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5250696539878845},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4978656768798828},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4850718080997467},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.46998822689056396},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4661492109298706},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4386731684207916},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43036267161369324},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42660945653915405},{"id":"https://openalex.org/keywords/data-driven","display_name":"Data-driven","score":0.4145659804344177},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.2938913106918335},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2574003338813782},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.23741599917411804}],"concepts":[{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.7824256420135498},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6995914578437805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6246525049209595},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6186337471008301},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.591688871383667},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5903066992759705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5779029726982117},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.5347935557365417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5250696539878845},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4978656768798828},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4850718080997467},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.46998822689056396},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4661492109298706},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4386731684207916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43036267161369324},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42660945653915405},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.4145659804344177},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2938913106918335},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2574003338813782},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.23741599917411804},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3085869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3085869","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:34129507","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34129507","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":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2684633063","display_name":null,"funder_award_id":"U1709211","funder_id":"https://openalex.org/F4320334064","funder_display_name":"National Natural Science Foundation of China-Zhejiang Joint Fund for the Integration of Industrialization and Informatization"},{"id":"https://openalex.org/G4287441911","display_name":null,"funder_award_id":"ICT2021B52","funder_id":"https://openalex.org/F4320326952","funder_display_name":"State Key Laboratory of Industrial Control Technology"},{"id":"https://openalex.org/G623490099","display_name":null,"funder_award_id":"U1709211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8980715636","display_name":null,"funder_award_id":"ICT2021A15","funder_id":"https://openalex.org/F4320326952","funder_display_name":"State Key Laboratory of Industrial Control Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326952","display_name":"State Key Laboratory of Industrial Control Technology","ror":null},{"id":"https://openalex.org/F4320334064","display_name":"National Natural Science Foundation of China-Zhejiang Joint Fund for the Integration of Industrialization and Informatization","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W567350711","https://openalex.org/W1731081199","https://openalex.org/W1959608418","https://openalex.org/W2000651380","https://openalex.org/W2013022059","https://openalex.org/W2032997274","https://openalex.org/W2047138503","https://openalex.org/W2104094955","https://openalex.org/W2105722058","https://openalex.org/W2112483442","https://openalex.org/W2115403315","https://openalex.org/W2125865219","https://openalex.org/W2131919105","https://openalex.org/W2159291411","https://openalex.org/W2165698076","https://openalex.org/W2187089797","https://openalex.org/W2188365844","https://openalex.org/W2504240155","https://openalex.org/W2539756354","https://openalex.org/W2556013418","https://openalex.org/W2625186681","https://openalex.org/W2757342969","https://openalex.org/W2789440825","https://openalex.org/W2892946488","https://openalex.org/W2897574832","https://openalex.org/W2900529838","https://openalex.org/W2909390529","https://openalex.org/W2913982144","https://openalex.org/W2955547856","https://openalex.org/W2957568672","https://openalex.org/W2963246109","https://openalex.org/W2963261224","https://openalex.org/W2963567641","https://openalex.org/W2965420085","https://openalex.org/W2971407654","https://openalex.org/W2982252423","https://openalex.org/W2988720209","https://openalex.org/W2995696070","https://openalex.org/W2999414995","https://openalex.org/W3014660087","https://openalex.org/W3014742123","https://openalex.org/W3015966228","https://openalex.org/W3018638193","https://openalex.org/W3020138377","https://openalex.org/W3047463300","https://openalex.org/W3049640903","https://openalex.org/W3080648230","https://openalex.org/W3131415659","https://openalex.org/W3164351180","https://openalex.org/W4288558759","https://openalex.org/W4320013936","https://openalex.org/W6637618735","https://openalex.org/W6640963894","https://openalex.org/W6676840641","https://openalex.org/W6678814708","https://openalex.org/W6683633756","https://openalex.org/W6687045409","https://openalex.org/W6761085173","https://openalex.org/W6772235576","https://openalex.org/W6776263648","https://openalex.org/W6776322687","https://openalex.org/W6782182507","https://openalex.org/W6791438039","https://openalex.org/W6795495158"],"related_works":["https://openalex.org/W1968523686","https://openalex.org/W298893735","https://openalex.org/W2199291344","https://openalex.org/W2938577525","https://openalex.org/W2887732792","https://openalex.org/W3203814031","https://openalex.org/W4287692411","https://openalex.org/W3047153562","https://openalex.org/W3177052839","https://openalex.org/W3080340002"],"abstract_inverted_index":{"Soft":[0],"sensors":[1,21],"have":[2],"been":[3],"extensively":[4],"developed":[5,79],"and":[6,28,61,86,114,129,167],"applied":[7],"in":[8,143,147],"the":[9,14,18,23,29,33,43,48,88,92,109,112,120,123,133,140,144,148,152,159,164,171,178],"process":[10,145],"industry.":[11],"One":[12],"of":[13,17,25,170,177],"main":[15],"challenges":[16],"data-driven":[19],"soft":[20,44,58,135],"is":[22,77,105,154,181],"lack":[24],"labeled":[26],"data":[27,125,146,161],"need":[30],"to":[31,41,57,80,107,131,157],"absorb":[32],"knowledge":[34,121],"from":[35,122],"a":[36,63,72,99],"related":[37],"source":[38,113,124],"operating":[39,150],"condition":[40],"enhance":[42,132],"sensing":[45],"performance":[46],"on":[47],"target":[49,115,134,149],"application.":[50],"This":[51],"article":[52],"introduces":[53],"deep":[54,64,73,172],"transfer":[55,66,103],"learning":[56],"sensor":[59,136],"modeling":[60],"proposes":[62],"probabilistic":[65,100],"regression":[67,75,89],"(DPTR)":[68],"framework.":[69,97],"In":[70],"DPTR,":[71],"generative":[74,173],"model":[76,87],"first":[78],"learn":[81],"Gaussian":[82],"latent":[83,101,116],"feature":[84],"representations":[85],"relationship":[90],"under":[91],"stochastic":[93],"gradient":[94],"variational":[95],"Bayes":[96],"Then,":[98],"space":[102],"strategy":[104],"designed":[106],"reduce":[108],"discrepancy":[110],"between":[111],"features":[117],"such":[118],"that":[119],"can":[126],"be":[127],"explored":[128],"transferred":[130],"performance.":[137],"Besides,":[138],"considering":[139],"missing":[141,160],"values":[142],"condition,":[151],"DPTR":[153],"further":[155],"extended":[156],"handle":[158],"problem":[162],"utilizing":[163],"strong":[165],"generation":[166],"reconstruction":[168],"capability":[169],"model.":[174],"The":[175],"effectiveness":[176],"proposed":[179],"method":[180],"validated":[182],"through":[183],"an":[184],"industrial":[185],"multiphase":[186],"flow":[187],"process.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":34},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":6}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
