{"id":"https://openalex.org/W4399374805","doi":"https://doi.org/10.1109/access.2024.3409899","title":"Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development","display_name":"Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399374805","doi":"https://doi.org/10.1109/access.2024.3409899"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3409899","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3409899","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3409899","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038422065","display_name":"Yurun Wang","orcid":"https://orcid.org/0000-0003-4536-2227"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou Normal University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yurun Wang","raw_affiliation_strings":["Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100741712","display_name":"Yi Huang","orcid":"https://orcid.org/0000-0001-6562-3100"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou Normal University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Huang","raw_affiliation_strings":["Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100758684","display_name":"Dongsheng Chen","orcid":"https://orcid.org/0000-0002-4486-0462"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou Normal University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Chen","raw_affiliation_strings":["Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017078233","display_name":"Longyan Wang","orcid":"https://orcid.org/0000-0002-8871-6569"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou Normal University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longyan Wang","raw_affiliation_strings":["Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028001200","display_name":"Lingjian Ye","orcid":"https://orcid.org/0000-0001-8732-593X"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou Normal University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjian Ye","raw_affiliation_strings":["Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8732-593X","affiliations":[{"raw_affiliation_string":"Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou, China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068929700","display_name":"Feifan Shen","orcid":"https://orcid.org/0000-0002-7086-6710"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]},{"id":"https://openalex.org/I4405254534","display_name":"NingboTech University","ror":"https://ror.org/01xx18q52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405254534"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feifan Shen","raw_affiliation_strings":["School of Information Science and Engineering, NingboTech University, Ningbo, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, NingboTech University, Ningbo, China","institution_ids":["https://openalex.org/I159389169","https://openalex.org/I4405254534"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2075,"currency":"USD","value_usd":2075},"apc_paid":{"value":2075,"currency":"USD","value_usd":2075},"fwci":0.9295,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78424291,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"12","issue":null,"first_page":"80633","last_page":"80645"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9779999852180481,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.7645481824874878},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5464571118354797},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5365580916404724},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5022990703582764},{"id":"https://openalex.org/keywords/soft-sensor","display_name":"Soft sensor","score":0.467936247587204},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3624117374420166},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3277862071990967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645481824874878},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5464571118354797},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5365580916404724},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5022990703582764},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.467936247587204},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3624117374420166},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3277862071990967},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3409899","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3409899","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a8e629f0c8444568adf3d6051dc5c57c","is_oa":true,"landing_page_url":"https://doaj.org/article/a8e629f0c8444568adf3d6051dc5c57c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 80633-80645 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3409899","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3409899","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G1990011851","display_name":null,"funder_award_id":"2023M730649","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G3606599647","display_name":null,"funder_award_id":"62103360","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6165907714","display_name":null,"funder_award_id":"62373147","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1504194272","https://openalex.org/W1522301498","https://openalex.org/W1968763291","https://openalex.org/W2006262045","https://openalex.org/W2085862958","https://openalex.org/W2130187411","https://openalex.org/W2135046866","https://openalex.org/W2157331557","https://openalex.org/W2161227280","https://openalex.org/W2509008543","https://openalex.org/W2588998538","https://openalex.org/W2742763523","https://openalex.org/W2788805965","https://openalex.org/W2805003733","https://openalex.org/W2889740942","https://openalex.org/W2920714358","https://openalex.org/W2962943048","https://openalex.org/W2971407654","https://openalex.org/W2980088075","https://openalex.org/W3001458159","https://openalex.org/W3015966228","https://openalex.org/W3025505824","https://openalex.org/W3025750776","https://openalex.org/W3043309535","https://openalex.org/W3080648230","https://openalex.org/W3081318531","https://openalex.org/W3123899295","https://openalex.org/W3157061921","https://openalex.org/W4212888625","https://openalex.org/W4244393449","https://openalex.org/W4285058963","https://openalex.org/W4285225889","https://openalex.org/W4287758389","https://openalex.org/W4304166167","https://openalex.org/W4308906783","https://openalex.org/W4310479533","https://openalex.org/W4310582202","https://openalex.org/W4312831725","https://openalex.org/W4317378116","https://openalex.org/W4323913758","https://openalex.org/W4327517926","https://openalex.org/W4361858459","https://openalex.org/W4387449023","https://openalex.org/W4387886008","https://openalex.org/W6631190155","https://openalex.org/W6751979845","https://openalex.org/W6771450561","https://openalex.org/W6779901144"],"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/W1964749215"],"abstract_inverted_index":{"For":[0],"deep":[1],"learning":[2],"based":[3],"soft":[4,163],"sensors,":[5],"the":[6,26,43,56,61,77,81,103,128,131,136,140,161,173,178],"spatiotemporal":[7],"attention":[8],"(STA)-LSTM":[9],"is":[10,67,74,86,125,142],"a":[11,68,87,106,151,155],"newly":[12],"emerged":[13],"technique":[14],"which":[15,35,66,91],"provides":[16],"efficient":[17],"predictions":[18],"for":[19,30,55,111,139],"quality":[20],"variables":[21],"of":[22,80,130],"industrial":[23,149],"processes.":[24],"However,":[25],"STA-LSTM":[27,57,120,141,174],"methods":[28],"calls":[29],"an":[31],"enormous":[32],"network":[33,38],"structure,":[34],"contains":[36],"redundant":[37],"weights":[39],"and":[40,135,154],"therefore":[41],"diminishing":[42],"model":[44,52],"generalization":[45],"ability.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50],"consider":[51],"sparse":[53,137],"representation":[54,138],"to":[58,71,116,144],"cope":[59],"with":[60],"above":[62],"problem.":[63],"The$\\ell":[64,83],"_{1}$-regularization,":[65],"popular":[69],"means":[70],"promote":[72],"sparsity,":[73],"introduced":[75],"into":[76],"loss":[78],"function":[79],"STA-LSTM.":[82],"_{1}$-regularized":[84,119],"formulation":[85],"non-smooth":[88,113],"optimization":[89,114],"problem,":[90],"cannot":[92],"be":[93],"well":[94,107],"solved":[95],"by":[96],"common":[97],"gradient":[98],"descent":[99],"approaches.":[100],"We":[101],"deploy":[102],"proximal":[104],"operator,":[105],"principled":[108],"mathematical":[109],"tool":[110],"handling":[112],"problems,":[115],"solve":[117],"the$\\ell":[118],"formulation.":[121],"The":[122,165],"new":[123,162],"algorithm":[124],"developed":[126],"within":[127],"framework":[129],"state-of-art":[132],"Adam":[133],"algorithm,":[134],"referred":[143],"as":[145],"Prox-STA-LSTM.":[146],"Finally,":[147],"two":[148],"cases,":[150],"carbon":[152],"absorber":[153],"desulfurization":[156],"process,":[157],"are":[158,181],"investigated":[159],"applying":[160],"sensor.":[164],"results":[166],"show":[167],"that":[168],"Prox-STA-LSTM":[169],"can":[170],"successfully":[171],"sparsify":[172],"networks.":[175],"More":[176],"importantly,":[177],"prediction":[179],"performances":[180],"also":[182],"enhanced.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
