{"id":"https://openalex.org/W2736810110","doi":"https://doi.org/10.1109/tac.2017.2727679","title":"Recursive Spectral Meta-Learner for Online Combining Different Fault Classifiers","display_name":"Recursive Spectral Meta-Learner for Online Combining Different Fault Classifiers","publication_year":2017,"publication_date":"2017-07-20","ids":{"openalex":"https://openalex.org/W2736810110","doi":"https://doi.org/10.1109/tac.2017.2727679","mag":"2736810110"},"language":"en","primary_location":{"id":"doi:10.1109/tac.2017.2727679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2017.2727679","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"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 Automatic 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/A5068635855","display_name":"Maoyin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maoyin Chen","raw_affiliation_strings":["Department of Automation, TNList, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8875-703X","affiliations":[{"raw_affiliation_string":"Department of Automation, TNList, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080674902","display_name":"Jun Shang","orcid":"https://orcid.org/0000-0003-0624-3655"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Shang","raw_affiliation_strings":["Department of Automation, TNList, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0624-3655","affiliations":[{"raw_affiliation_string":"Department of Automation, TNList, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.6122,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69428046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"63","issue":"2","first_page":"586","last_page":"593"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9997000098228455,"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":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901000261306763,"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/T12676","display_name":"Machine Learning and ELM","score":0.9901000261306763,"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/random-subspace-method","display_name":"Random subspace method","score":0.6515573263168335},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.5637954473495483},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5626494288444519},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5609327554702759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5199317336082458},{"id":"https://openalex.org/keywords/conditional-dependence","display_name":"Conditional dependence","score":0.5119494199752808},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5052316784858704},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.47945988178253174},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.47829514741897583},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45084148645401},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.44953611493110657},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4463193714618683},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44600242376327515},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4301193058490753},{"id":"https://openalex.org/keywords/binary-decision-diagram","display_name":"Binary decision diagram","score":0.41660240292549133},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41063833236694336},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32110732793807983},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1351194679737091}],"concepts":[{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.6515573263168335},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.5637954473495483},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5626494288444519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5609327554702759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5199317336082458},{"id":"https://openalex.org/C174920663","wikidata":"https://www.wikidata.org/wiki/Q5159256","display_name":"Conditional dependence","level":2,"score":0.5119494199752808},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5052316784858704},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.47945988178253174},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.47829514741897583},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45084148645401},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.44953611493110657},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4463193714618683},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44600242376327515},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4301193058490753},{"id":"https://openalex.org/C3309909","wikidata":"https://www.wikidata.org/wiki/Q864155","display_name":"Binary decision diagram","level":2,"score":0.41660240292549133},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41063833236694336},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32110732793807983},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1351194679737091},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tac.2017.2727679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2017.2727679","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"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 Automatic Control","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G8732448410","display_name":null,"funder_award_id":"61473164","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":23,"referenced_works":["https://openalex.org/W1597576211","https://openalex.org/W1768443527","https://openalex.org/W1967904638","https://openalex.org/W1970537494","https://openalex.org/W1988455509","https://openalex.org/W1991137221","https://openalex.org/W1991519797","https://openalex.org/W1997129315","https://openalex.org/W2004186751","https://openalex.org/W2010464263","https://openalex.org/W2072597598","https://openalex.org/W2100028154","https://openalex.org/W2158958729","https://openalex.org/W2266777744","https://openalex.org/W2309693750","https://openalex.org/W2397271794","https://openalex.org/W2554839354","https://openalex.org/W2599795618","https://openalex.org/W2611328865","https://openalex.org/W2795771040","https://openalex.org/W3100800287","https://openalex.org/W4232841423","https://openalex.org/W4312258136"],"related_works":["https://openalex.org/W2320442256","https://openalex.org/W2052615004","https://openalex.org/W4300631294","https://openalex.org/W2390183607","https://openalex.org/W2122917767","https://openalex.org/W3196342125","https://openalex.org/W86917440","https://openalex.org/W1819373035","https://openalex.org/W2188215366","https://openalex.org/W4309156034"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"the":[3,37,53,65,69,72,79,92,98,114,126,145],"problem":[4],"of":[5,46,68,71,104,116,122,139],"fault":[6,10],"classification":[7,40,55],"when":[8],"different":[9,43,50,123],"classifiers":[11,124],"are":[12],"performed":[13],"simultaneously.":[14],"Based":[15],"on":[16,125],"spectral":[17],"meta-learner":[18],"(SML)":[19],"proposed":[20],"by":[21,144],"Parisi":[22],"et":[23],"al.,":[24],"its":[25],"recursive":[26,29,117],"version,":[27],"i.e.,":[28],"SML":[30],"(RSML)":[31],"is":[32,57,76,87,106],"developed":[33],"for":[34,82,90],"online":[35,99],"combining":[36],"potentially":[38],"conflicting":[39],"information.":[41],"Considering":[42],"statistical":[44,111],"properties":[45],"faults":[47],"occurring":[48],"at":[49],"time":[51],"intervals,":[52],"binary":[54],"information":[56],"recursively":[58],"utilized.":[59],"By":[60],"introducing":[61],"a":[62,110,135],"forgetting":[63],"factor,":[64],"leading":[66],"eigenvector":[67,93],"estimate":[70],"time-varying":[73],"covariance":[74],"matrix":[75],"used":[77,89],"as":[78],"weight":[80,127],"vector":[81],"each":[83],"classifier.":[84],"Rank-one":[85],"modification":[86],"then":[88],"calculating":[91],"in":[94,109],"order":[95],"to":[96],"reduce":[97],"computational":[100],"complexity.":[101],"The":[102],"performance":[103],"RSML":[105,140],"strictly":[107],"analyzed":[108],"sense,":[112],"including":[113],"effect":[115],"calculation":[118],"and":[119,133],"conditional":[120],"dependence":[121],"vector.":[128],"Compared":[129],"with":[130],"majority":[131],"voting":[132],"SML,":[134],"higher":[136],"balanced":[137],"accuracy":[138],"can":[141],"be":[142],"verified":[143],"benchmark":[146],"Tennessee":[147],"Eastman":[148],"process.":[149]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}