{"id":"https://openalex.org/W3082184637","doi":"https://doi.org/10.1109/tii.2020.3021047","title":"Cooperative Deep Dynamic Feature Extraction and Variable Time-Delay Estimation for Industrial Quality Prediction","display_name":"Cooperative Deep Dynamic Feature Extraction and Variable Time-Delay Estimation for Industrial Quality Prediction","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3082184637","doi":"https://doi.org/10.1109/tii.2020.3021047","mag":"3082184637"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2020.3021047","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.3021047","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/A5035755593","display_name":"Le Yao","orcid":"https://orcid.org/0000-0002-0881-213X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]},{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Le Yao","raw_affiliation_strings":["Peng Cheng Laboratory, Control Science and Engineering, Zhejiang University, Shenzhen, China","State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Control Science and Engineering, Zhejiang University, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I76130692"]},{"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":"last","author":{"id":"https://openalex.org/A5067726465","display_name":"Zhiqiang Ge","orcid":"https://orcid.org/0000-0002-2071-4380"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I4391767838","display_name":"State Key Laboratory of Industrial Control Technology","ror":"https://ror.org/03a33a786","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767838","https://openalex.org/I76130692"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Ge","raw_affiliation_strings":["Peng Cheng Laboratory, Control Science and Engineering, Zhejiang University, Shenzhen, China","State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Control Science and Engineering, Zhejiang University, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I76130692"]},{"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"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035755593"],"corresponding_institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I4391767838","https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":5.3417,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.96216873,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"17","issue":"6","first_page":"3782","last_page":"3792"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9991000294685364,"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":0.9991000294685364,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.987500011920929,"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"}},{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9807000160217285,"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/feature-extraction","display_name":"Feature extraction","score":0.6505799889564514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.643256664276123},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6005155444145203},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.584629237651825},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5643062591552734},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5416285395622253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49279406666755676},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4802837073802948},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4631267189979553},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.434828519821167},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.42722588777542114},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4178485572338104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.408652126789093},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39150068163871765},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19634678959846497},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1780153512954712}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6505799889564514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.643256664276123},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6005155444145203},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.584629237651825},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5643062591552734},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5416285395622253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49279406666755676},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4802837073802948},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4631267189979553},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.434828519821167},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.42722588777542114},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4178485572338104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.408652126789093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39150068163871765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19634678959846497},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1780153512954712},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2020.3021047","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2020.3021047","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","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G1987348790","display_name":null,"funder_award_id":"61833014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2458964202","display_name":null,"funder_award_id":"zj2019008","funder_id":"https://openalex.org/F4320317779","funder_display_name":"Zhejiang\u00a0Provincial\u00a0Postdoctoral\u00a0Science\u00a0Foundation"},{"id":"https://openalex.org/G7875806344","display_name":null,"funder_award_id":"61722310","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8342248566","display_name":null,"funder_award_id":"2019M662050","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320317779","display_name":"Zhejiang\u00a0Provincial\u00a0Postdoctoral\u00a0Science\u00a0Foundation","ror":null},{"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1997175427","https://openalex.org/W2029592171","https://openalex.org/W2049691667","https://openalex.org/W2055840446","https://openalex.org/W2085654536","https://openalex.org/W2085862958","https://openalex.org/W2127416468","https://openalex.org/W2201252546","https://openalex.org/W2319940424","https://openalex.org/W2539756354","https://openalex.org/W2555972346","https://openalex.org/W2600788304","https://openalex.org/W2602750048","https://openalex.org/W2606776959","https://openalex.org/W2741800562","https://openalex.org/W2742763523","https://openalex.org/W2745057892","https://openalex.org/W2762324647","https://openalex.org/W2773984145","https://openalex.org/W2789416742","https://openalex.org/W2854109523","https://openalex.org/W2889017122","https://openalex.org/W2891488123","https://openalex.org/W2919235887","https://openalex.org/W2920714358","https://openalex.org/W2971407654","https://openalex.org/W2986815055","https://openalex.org/W2987175304","https://openalex.org/W3004547709","https://openalex.org/W3034110392","https://openalex.org/W6657710722"],"related_works":["https://openalex.org/W3018365851","https://openalex.org/W3207484021","https://openalex.org/W2038693912","https://openalex.org/W3123600015","https://openalex.org/W1991602789","https://openalex.org/W136259318","https://openalex.org/W1582396021","https://openalex.org/W2807783496","https://openalex.org/W2016200266","https://openalex.org/W2051452952"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"a":[3,41],"novel":[4],"data-driven":[5],"industrial":[6],"quality":[7,46,67],"predictor":[8],"is":[9,31],"proposed":[10,33,127,141],"based":[11],"on":[12],"the":[13,50,72,82,87,98,102,112,116,122,126,137,140],"cooperative":[14],"deep":[15],"dynamic":[16,26,37],"feature":[17,27],"extraction":[18],"and":[19,54,66,75,94],"variable":[20],"time-delay":[21],"(VTD)":[22],"estimation.":[23,145],"A":[24],"semisupervised":[25],"extracting":[28],"(SSDFE)":[29],"network":[30,104],"first":[32],"to":[34,39,49,135],"extract":[35],"nonlinear":[36],"features":[38],"build":[40],"regression":[42],"model":[43,92],"for":[44],"output":[45],"prediction.":[47],"Due":[48],"inherent":[51],"process":[52,64,84,100],"structure":[53],"different":[55],"positions":[56],"of":[57,101,125,139],"sampling":[58],"instruments,":[59],"time-delays":[60],"commonly":[61],"exist":[62],"between":[63],"variables":[65],"variables,":[68],"which":[69],"may":[70],"distort":[71],"original":[73,83],"distribution":[74],"relationship":[76],"in":[77,97],"collected":[78],"data.":[79],"To":[80],"recover":[81],"data":[85],"pattern,":[86],"VTDs":[88],"are":[89,133],"regarded":[90],"as":[91],"parameters":[93],"cooperatively":[95],"obtained":[96],"training":[99],"SSDFE":[103,128],"through":[105],"an":[106],"integer":[107],"differential":[108],"evolution":[109],"algorithm.":[110],"With":[111],"estimated":[113],"VTD":[114,144],"values,":[115],"reconstructed":[117],"dataset":[118],"further":[119],"helps":[120],"improve":[121],"prediction":[123],"performance":[124],"network.":[129],"Two":[130],"case":[131],"studies":[132],"presented":[134],"demonstrate":[136],"superiority":[138],"method":[142],"with":[143]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":10}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}
