{"id":"https://openalex.org/W4214676882","doi":"https://doi.org/10.1109/tim.2022.3152856","title":"A Supervised Bidirectional Long Short-Term Memory Network for Data-Driven Dynamic Soft Sensor Modeling","display_name":"A Supervised Bidirectional Long Short-Term Memory Network for Data-Driven Dynamic Soft Sensor Modeling","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4214676882","doi":"https://doi.org/10.1109/tim.2022.3152856"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3152856","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2022.3152856","pdf_url":"https://ieeexplore.ieee.org/ielx7/19/9717300/09718226.pdf","source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/19/9717300/09718226.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072936696","display_name":"Chun Fai Lui","orcid":"https://orcid.org/0000-0002-2379-0821"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Chun Fai Lui","raw_affiliation_strings":["Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-2379-0821","affiliations":[{"raw_affiliation_string":"Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100744924","display_name":"Yiqi Liu","orcid":"https://orcid.org/0000-0001-8911-727X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]},{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["CN","DK"],"is_corresponding":false,"raw_author_name":"Yiqi Liu","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","Process and Systems Engineering Center (PROSYS), Technical University of Denmark, Lyngby, Denmark"],"raw_orcid":"https://orcid.org/0000-0001-8911-727X","affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Process and Systems Engineering Center (PROSYS), Technical University of Denmark, Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070592593","display_name":"Min Xie","orcid":"https://orcid.org/0000-0002-8500-8364"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Min Xie","raw_affiliation_strings":["Department of Advanced Design and Systems Engineering and the School of Data Science, City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-8500-8364","affiliations":[{"raw_affiliation_string":"Department of Advanced Design and Systems Engineering and the School of Data Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.4033,"has_fulltext":true,"cited_by_count":178,"citation_normalized_percentile":{"value":0.99710546,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9991999864578247,"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":0.9991999864578247,"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/T10320","display_name":"Neural Networks and Applications","score":0.994700014591217,"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/T10791","display_name":"Advanced Control Systems Optimization","score":0.9797999858856201,"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":0.6158795952796936},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5838045477867126},{"id":"https://openalex.org/keywords/soft-sensor","display_name":"Soft sensor","score":0.46522045135498047},{"id":"https://openalex.org/keywords/dynamic-random-access-memory","display_name":"Dynamic random-access memory","score":0.42803096771240234},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3522565960884094},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.33925533294677734},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19651669263839722},{"id":"https://openalex.org/keywords/semiconductor-memory","display_name":"Semiconductor memory","score":0.1573163866996765},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.15025857090950012}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6158795952796936},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5838045477867126},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.46522045135498047},{"id":"https://openalex.org/C118702147","wikidata":"https://www.wikidata.org/wiki/Q189396","display_name":"Dynamic random-access memory","level":3,"score":0.42803096771240234},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3522565960884094},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33925533294677734},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19651669263839722},{"id":"https://openalex.org/C98986596","wikidata":"https://www.wikidata.org/wiki/Q1143031","display_name":"Semiconductor memory","level":2,"score":0.1573163866996765},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.15025857090950012},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tim.2022.3152856","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2022.3152856","pdf_url":"https://ieeexplore.ieee.org/ielx7/19/9717300/09718226.pdf","source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/725a767e-f765-4d41-a5a0-b7a3d9ea5103","is_oa":true,"landing_page_url":"https://hdl.handle.net/2031/725a767e-f765-4d41-a5a0-b7a3d9ea5103","pdf_url":"https://scholars.cityu.edu.hk/files/104516229/A_Supervised_Bidirectional_Long_Short_Term_Memory_Network_for_Data_Driven_Dynamic_Soft_Sensor_Modeling.pdf","source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Lui, C F, Liu, Y & Xie, M 2022, 'A Supervised Bidirectional Long Short-Term Memory Network for Data-driven Dynamic Soft Sensor Modeling', IEEE Transactions on Instrumentation and Measurement, vol. 71, 2504713. https://doi.org/10.1109/TIM.2022.3152856","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:pure.atira.dk:publications/2c66951d-97ea-43e9-be57-0def201bb823","is_oa":true,"landing_page_url":"https://orbit.dtu.dk/en/publications/2c66951d-97ea-43e9-be57-0def201bb823","pdf_url":null,"source":{"id":"https://openalex.org/S4306400705","display_name":"Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I96673099","host_organization_name":"Technical University of Denmark","host_organization_lineage":["https://openalex.org/I96673099"],"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":"Fai Lui , C , Liu , Y &amp; Xie , M 2022 , ' A Supervised Bidirectional Long Short-Term Memory Network for Data-driven Dynamic Soft Sensor Modeling ' , IEEE Transactions on Instrumentation and Measurement , vol. 71 , 2504713 . https://doi.org/10.1109/TIM.2022.3152856","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/tim.2022.3152856","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2022.3152856","pdf_url":"https://ieeexplore.ieee.org/ielx7/19/9717300/09718226.pdf","source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation","score":0.8600000143051147}],"awards":[{"id":"https://openalex.org/G2847445062","display_name":"Importance analysis and maintenance decisions of complex systems with dependent components","funder_award_id":"11203519","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G5720761930","display_name":null,"funder_award_id":"72032005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7979949094","display_name":"\u57fa\u4e8e\u90e8\u4ef6\u76f8\u4f9d\u7684\u590d\u6742\u7cfb\u7edf\u5269\u4f59\u5bff\u547d\u5efa\u6a21\u53ca\u9884\u6d4b\u6027\u7ef4\u4fee\u7b56\u7565\u7814\u7a76","funder_award_id":"71971181","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8226490486","display_name":null,"funder_award_id":"9360163","funder_id":"https://openalex.org/F4320334123","funder_display_name":"Hong Kong Institute for Data Science"},{"id":"https://openalex.org/G836235620","display_name":"New Approaches for Reliability Analysis of Industrial Systems Subject to Multivariate Degradation","funder_award_id":"11200621","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320321920","display_name":"Innovation and Technology Commission","ror":"https://ror.org/04vf9tr09"},{"id":"https://openalex.org/F4320334123","display_name":"Hong Kong Institute for Data Science","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214676882.pdf","grobid_xml":"https://content.openalex.org/works/W4214676882.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W623776627","https://openalex.org/W1689711448","https://openalex.org/W2137356002","https://openalex.org/W2466822794","https://openalex.org/W2570309338","https://openalex.org/W2777815485","https://openalex.org/W2786583476","https://openalex.org/W2897657100","https://openalex.org/W2920714358","https://openalex.org/W2921849857","https://openalex.org/W2942496699","https://openalex.org/W2956566815","https://openalex.org/W2964543633","https://openalex.org/W2971407654","https://openalex.org/W2980608982","https://openalex.org/W2980736546","https://openalex.org/W2987175304","https://openalex.org/W3002630677","https://openalex.org/W3007682521","https://openalex.org/W3015790446","https://openalex.org/W3016077482","https://openalex.org/W3016192422","https://openalex.org/W3043785945","https://openalex.org/W3049769422","https://openalex.org/W3091264179","https://openalex.org/W3094733926","https://openalex.org/W3120740533","https://openalex.org/W3123899295","https://openalex.org/W3126304207","https://openalex.org/W3152632945","https://openalex.org/W3157761116","https://openalex.org/W3158936052","https://openalex.org/W3196610154","https://openalex.org/W3199803535","https://openalex.org/W4200470568","https://openalex.org/W6678534324"],"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/W3152705324","https://openalex.org/W2359154573","https://openalex.org/W2737942854","https://openalex.org/W1496210503"],"abstract_inverted_index":{"Data-driven":[0],"soft":[1,47,65,128,159],"sensors":[2],"have":[3],"been":[4],"widely":[5],"adopted":[6],"in":[7,46],"industrial":[8,144],"processes":[9],"to":[10,19,25,79],"learn":[11],"hidden":[12],"knowledge":[13],"automatically":[14],"from":[15,107],"process":[16,109,141],"data,":[17],"then":[18,114],"monitor":[20],"difficult-to-measure":[21],"quality":[22,36,72,112],"variables.":[23],"However,":[24],"extract":[26,100],"and":[27,86,101,111,142,155],"utilize":[28,102],"useful":[29],"dynamic":[30,64,104],"latent":[31,105],"features":[32],"accurately":[33],"for":[34,62],"efficient":[35],"estimations":[37],"remains":[38],"one":[39],"of":[40,123],"the":[41,97,117,124,151],"most":[42],"important":[43],"research":[44],"issues":[45],"sensor":[48,66,129,160],"modeling.":[49,67],"In":[50],"this":[51,94],"article,":[52],"a":[53,75,138],"supervised":[54],"bidirectional":[55,91],"long":[56],"short-term":[57],"memory":[58],"(SBiLSTM)":[59],"is":[60,131],"proposed":[61,125],"data-driven":[63],"The":[68,121],"SBiLSTM":[69,98,126,152],"incorporates":[70],"extended":[71],"information":[73,106],"with":[74],"moving":[76],"window":[77],"up":[78],"<inline-formula>":[80],"<tex-math":[81],"notation=\"LaTeX\">$k$":[82],"</tex-math></inline-formula>":[83],"time":[84],"steps":[85],"enhances":[87],"learning":[88],"efficiency":[89],"by":[90],"architecture.":[92],"With":[93],"novel":[95],"structure,":[96],"can":[99],"nonlinear":[103],"both":[108],"variables":[110],"variables,":[113],"further":[115],"improve":[116],"prediction":[118],"performance":[119],"significantly.":[120],"effectiveness":[122],"network-based":[127],"model":[130],"demonstrated":[132],"through":[133],"two":[134],"case":[135],"studies":[136],"on":[137],"debutanizer":[139],"column":[140],"an":[143],"wastewater":[145],"treatment":[146],"process.":[147],"Results":[148],"show":[149],"that":[150],"outperforms":[153],"state-of-the-art":[154],"traditional":[156],"deep":[157],"learning-based":[158],"models.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":21},{"year":2025,"cited_by_count":61},{"year":2024,"cited_by_count":46},{"year":2023,"cited_by_count":38},{"year":2022,"cited_by_count":12}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}
