{"id":"https://openalex.org/W4200196658","doi":"https://doi.org/10.1177/01423312211060576","title":"A multimode process monitoring strategy via improved variational inference Gaussian mixture model based on locality preserving projections","display_name":"A multimode process monitoring strategy via improved variational inference Gaussian mixture model based on locality preserving projections","publication_year":2021,"publication_date":"2021-12-10","ids":{"openalex":"https://openalex.org/W4200196658","doi":"https://doi.org/10.1177/01423312211060576"},"language":"en","primary_location":{"id":"doi:10.1177/01423312211060576","is_oa":false,"landing_page_url":"https://doi.org/10.1177/01423312211060576","pdf_url":null,"source":{"id":"https://openalex.org/S24148485","display_name":"Transactions of the Institute of Measurement and Control","issn_l":"0142-3312","issn":["0142-3312","1477-0369"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Institute of Measurement and Control","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/A5108477160","display_name":"Qingxiu Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingxiu Guo","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0002-2801-8312","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071371875","display_name":"Jianchang Liu","orcid":"https://orcid.org/0000-0002-2801-8312"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianchang Liu","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100700480","display_name":"Shubin Tan","orcid":"https://orcid.org/0000-0003-0580-1387"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shubin Tan","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031576307","display_name":"Dongsheng Yang","orcid":"https://orcid.org/0000-0003-1262-5975"},"institutions":[{"id":"https://openalex.org/I48780066","display_name":"Shenyang University of Chemical Technology","ror":"https://ror.org/03dbpdh75","country_code":"CN","type":"education","lineage":["https://openalex.org/I48780066"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Yang","raw_affiliation_strings":["College of Information Science and Engineering, Shenyang University of Chemical Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Shenyang University of Chemical Technology, China","institution_ids":["https://openalex.org/I48780066"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100618717","display_name":"Yuan Li","orcid":"https://orcid.org/0000-0001-7466-9485"},"institutions":[{"id":"https://openalex.org/I48780066","display_name":"Shenyang University of Chemical Technology","ror":"https://ror.org/03dbpdh75","country_code":"CN","type":"education","lineage":["https://openalex.org/I48780066"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Li","raw_affiliation_strings":["College of Information Science and Engineering, Shenyang University of Chemical Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-7466-9485","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Shenyang University of Chemical Technology, China","institution_ids":["https://openalex.org/I48780066"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100439726","display_name":"Cheng Zhang","orcid":"https://orcid.org/0009-0008-2021-6016"},"institutions":[{"id":"https://openalex.org/I48780066","display_name":"Shenyang University of Chemical Technology","ror":"https://ror.org/03dbpdh75","country_code":"CN","type":"education","lineage":["https://openalex.org/I48780066"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Zhang","raw_affiliation_strings":["College of Information Science and Engineering, Shenyang University of Chemical Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Shenyang University of Chemical Technology, China","institution_ids":["https://openalex.org/I48780066"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5071371875"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":1.1102,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78123052,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"44","issue":"9","first_page":"1732","last_page":"1743"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9998000264167786,"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":0.9998000264167786,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5633019208908081},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5308226943016052},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5153017044067383},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.506222665309906},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4926808476448059},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.48980140686035156},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4768979549407959},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.46078503131866455},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.46057865023612976},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.36999306082725525},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3490517735481262},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32788097858428955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2987736463546753},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14059185981750488}],"concepts":[{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5633019208908081},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5308226943016052},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5153017044067383},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.506222665309906},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4926808476448059},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.48980140686035156},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4768979549407959},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.46078503131866455},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.46057865023612976},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.36999306082725525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3490517735481262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32788097858428955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2987736463546753},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14059185981750488},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/01423312211060576","is_oa":false,"landing_page_url":"https://doi.org/10.1177/01423312211060576","pdf_url":null,"source":{"id":"https://openalex.org/S24148485","display_name":"Transactions of the Institute of Measurement and Control","issn_l":"0142-3312","issn":["0142-3312","1477-0369"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Institute of Measurement and Control","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G8793657544","display_name":null,"funder_award_id":"61773106","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1506806321","https://openalex.org/W1971663396","https://openalex.org/W1993267542","https://openalex.org/W2004186751","https://openalex.org/W2018326367","https://openalex.org/W2033910531","https://openalex.org/W2036887017","https://openalex.org/W2049633694","https://openalex.org/W2072974424","https://openalex.org/W2120211304","https://openalex.org/W2139833307","https://openalex.org/W2157012916","https://openalex.org/W2165072487","https://openalex.org/W2225156818","https://openalex.org/W2757109865","https://openalex.org/W2805344434","https://openalex.org/W2883342032","https://openalex.org/W2884121498","https://openalex.org/W2897534289","https://openalex.org/W2899505897","https://openalex.org/W2918460052","https://openalex.org/W2943893658","https://openalex.org/W2974000087","https://openalex.org/W2977049471","https://openalex.org/W2981337591","https://openalex.org/W2983406044","https://openalex.org/W2989600764","https://openalex.org/W2997570517","https://openalex.org/W3001165160","https://openalex.org/W3012499179","https://openalex.org/W3012626305","https://openalex.org/W3026409547","https://openalex.org/W3089463203","https://openalex.org/W3091068909","https://openalex.org/W3093377502","https://openalex.org/W3103002366","https://openalex.org/W3104577407","https://openalex.org/W3111312859","https://openalex.org/W3114979514","https://openalex.org/W3127688238","https://openalex.org/W4205530313"],"related_works":["https://openalex.org/W1556451512","https://openalex.org/W1555349535","https://openalex.org/W4234091740","https://openalex.org/W4213350282","https://openalex.org/W2230171082","https://openalex.org/W2583128298","https://openalex.org/W2022275305","https://openalex.org/W1604115909","https://openalex.org/W2369125128","https://openalex.org/W2134423494"],"abstract_inverted_index":{"For":[0],"multimode":[1,29],"process":[2,30,151,170],"monitoring,":[3],"accurate":[4],"mode":[5,14,142],"information":[6],"is":[7,15,69,113,125],"difficult":[8],"to":[9,52,71,105,115,127],"be":[10],"obtained,":[11],"and":[12,152,165],"each":[13],"monitored":[16],"separately,":[17],"which":[18,144],"increases":[19],"the":[20,23,47,53,60,73,76,81,85,89,98,106,110,117,123,129,137,141,146,149,154,166,172],"complexity":[21,147],"of":[22,75,100,120,139,148,161,174],"system.":[24],"This":[25],"paper":[26],"proposes":[27],"a":[28,65,162],"monitoring":[31,136,150],"strategy":[32],"via":[33],"improved":[34],"variational":[35],"inference":[36],"Gaussian":[37],"mixture":[38],"model":[39,134],"based":[40],"on":[41,80],"locality":[42],"preserving":[43],"projections":[44],"(IVIGMM-LPP).":[45],"First,":[46],"raw":[48],"data":[49,90],"are":[50,91,103],"projected":[51],"feature":[54],"space":[55],"where":[56],"samples":[57],"still":[58],"maintain":[59],"original":[61],"neighbor":[62],"structure.":[63],"Second,":[64],"new":[66],"discriminant":[67],"condition":[68],"introduced":[70,114],"reduce":[72],"influence":[74],"initial":[77],"category":[78],"parameter":[79],"iteration":[82],"results":[83,160],"in":[84],"VIGMM":[86],"model.":[87],"Then,":[88],"updated":[92],"utilizing":[93],"modal":[94],"information,":[95,143],"so":[96],"that":[97],"scales":[99],"different":[101],"modes":[102],"adjusted":[104],"same":[107],"level.":[108],"Next,":[109],"deviation":[111],"vector":[112],"eliminate":[116],"multi-center":[118],"structure":[119],"data.":[121],"Finally,":[122],"statistic":[124],"built":[126],"monitor":[128],"process.":[130],"IVIGMM-LPP":[131],"establishes":[132],"one":[133],"for":[135],"premise":[138],"knowing":[140],"reduces":[145],"improves":[153],"fault":[155],"detection":[156],"rate.":[157],"The":[158],"experimental":[159],"numerical":[163],"case":[164],"Tennessee":[167],"Eastman":[168],"(TE)":[169],"verify":[171],"effectiveness":[173],"IVIGMM-LPP.":[175]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
