{"id":"https://openalex.org/W4414499403","doi":"https://doi.org/10.1109/tcyb.2025.3610475","title":"Principal Predictor Analysis With Application to Dynamic Process Monitoring","display_name":"Principal Predictor Analysis With Application to Dynamic Process Monitoring","publication_year":2025,"publication_date":"2025-09-25","ids":{"openalex":"https://openalex.org/W4414499403","doi":"https://doi.org/10.1109/tcyb.2025.3610475","pmid":"https://pubmed.ncbi.nlm.nih.gov/40997004"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2025.3610475","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tcyb.2025.3610475","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tcyb.2025.3610475","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shumei Chen","orcid":"https://orcid.org/0009-0007-5710-343X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shumei Chen","raw_affiliation_strings":["School of Data Science, Lingnan University, Hong Kong, China","School of Data Science, Lingnan University, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0009-0007-5710-343X","affiliations":[{"raw_affiliation_string":"School of Data Science, Lingnan University, Hong Kong, China","institution_ids":[]},{"raw_affiliation_string":"School of Data Science, Lingnan University, Hong Kong, Hong Kong","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056937548","display_name":"S. Joe Qin","orcid":"https://orcid.org/0000-0001-7631-2535"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S. Joe Qin","raw_affiliation_strings":["School of Data Science, Lingnan University, Hong Kong, China","School of Data Science, Lingnan University, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7631-2535","affiliations":[{"raw_affiliation_string":"School of Data Science, Lingnan University, Hong Kong, China","institution_ids":[]},{"raw_affiliation_string":"School of Data Science, Lingnan University, Hong Kong, Hong Kong","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9042,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78620824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"56","issue":"1","first_page":"460","last_page":"472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9305999875068665,"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":0.9305999875068665,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.796500027179718},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6069999933242798},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5825999975204468},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.534500002861023},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5189999938011169},{"id":"https://openalex.org/keywords/functional-principal-component-analysis","display_name":"Functional principal component analysis","score":0.5113999843597412},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.49709999561309814},{"id":"https://openalex.org/keywords/principal","display_name":"Principal (computer security)","score":0.45980000495910645}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.796500027179718},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6069999933242798},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5825999975204468},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.534500002861023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.529699981212616},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5189999938011169},{"id":"https://openalex.org/C71176878","wikidata":"https://www.wikidata.org/wiki/Q17014987","display_name":"Functional principal component analysis","level":3,"score":0.5113999843597412},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.49709999561309814},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4666000008583069},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.45980000495910645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3634999990463257},{"id":"https://openalex.org/C74887250","wikidata":"https://www.wikidata.org/wiki/Q3455892","display_name":"Principal component regression","level":3,"score":0.3499000072479248},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C2987333383","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process dynamics","level":3,"score":0.32760000228881836},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3188000023365021},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3034000098705292},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.28369998931884766},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.2750999927520752}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2025.3610475","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tcyb.2025.3610475","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},{"id":"pmid:40997004","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40997004","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":{"id":"doi:10.1109/tcyb.2025.3610475","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tcyb.2025.3610475","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1978403823","https://openalex.org/W2002268936","https://openalex.org/W2017257315","https://openalex.org/W2020737422","https://openalex.org/W2038395331","https://openalex.org/W2057283314","https://openalex.org/W2100495367","https://openalex.org/W2103110513","https://openalex.org/W2122538988","https://openalex.org/W2125027820","https://openalex.org/W2135086139","https://openalex.org/W2140327685","https://openalex.org/W2156141384","https://openalex.org/W2169347809","https://openalex.org/W2194542308","https://openalex.org/W2252403014","https://openalex.org/W2294798173","https://openalex.org/W2342028629","https://openalex.org/W2432567885","https://openalex.org/W2498094064","https://openalex.org/W2626923521","https://openalex.org/W2765130047","https://openalex.org/W2774636206","https://openalex.org/W2788023040","https://openalex.org/W2947626232","https://openalex.org/W2963724581","https://openalex.org/W2964242306","https://openalex.org/W3000195460","https://openalex.org/W3010705831","https://openalex.org/W3040514440","https://openalex.org/W3092838682","https://openalex.org/W3163178155","https://openalex.org/W3171633131","https://openalex.org/W3179303890","https://openalex.org/W3197686036","https://openalex.org/W4220772834","https://openalex.org/W4238805501","https://openalex.org/W4249625715","https://openalex.org/W4283221088","https://openalex.org/W4285246487","https://openalex.org/W4298082496","https://openalex.org/W4313270785","https://openalex.org/W4386970263","https://openalex.org/W4391020760","https://openalex.org/W4411405277","https://openalex.org/W4412419669"],"related_works":[],"abstract_inverted_index":{"Modern":[0],"engineering":[1],"and":[2,18,104,117,126,132],"scientific":[3],"systems":[4],"are":[5,47,119],"usually":[6],"equipped":[7],"with":[8,32,79,93,113],"abundant":[9],"sensors":[10],"to":[11,35,87,97,135,140],"collect":[12],"large-dimensional":[13,41],"time":[14,42],"series":[15,43],"for":[16,99],"monitoring":[17,90,95,116],"operations.":[19],"In":[20],"this":[21],"article,":[22],"we":[23],"develop":[24],"a":[25],"novel":[26],"principal":[27,61],"predictor":[28,38],"analysis":[29,63],"(PPA)":[30],"framework":[31],"reduced-dimensional":[33],"dynamics":[34],"obtain":[36],"parsimonious":[37],"models":[39],"of":[40,53],"data.":[44],"Principal":[45],"predictors":[46,103],"obtained":[48],"by":[49],"maximizing":[50],"the":[51,67,71,80,102,105,127],"variance":[52],"predictions":[54],"from":[55],"their":[56,142],"past":[57],"values.":[58],"Unlike":[59],"classical":[60],"component":[62],"(PCA),":[64],"which":[65,108],"reduces":[66],"dimensionality":[68],"without":[69],"emphasizing":[70],"prediction,":[72],"PPA":[73,85],"focuses":[74],"on":[75],"extracting":[76],"latent":[77],"variables":[78],"maximum":[81],"predictive":[82,94],"capability.":[83],"The":[84],"application":[86],"dynamic":[88],"process":[89],"is":[91],"performed":[92],"indices":[96],"account":[98],"variations":[100],"in":[101,121],"unpredicted":[106],"residuals,":[107],"can":[109],"be":[110],"subsequently":[111],"modeled":[112],"PCA.":[114],"PPA-based":[115],"diagnosis":[118],"demonstrated":[120],"an":[122,133],"illustrative":[123],"closed-loop":[124],"system":[125],"industrial":[128],"Dow":[129],"Challenge":[130],"Problem":[131],"extension":[134],"include":[136],"known":[137],"first-principles":[138],"relations":[139],"show":[141],"effectiveness.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}