{"id":"https://openalex.org/W2018411202","doi":"https://doi.org/10.1109/tie.2014.2385042","title":"Mixture Bayesian Regularization of PCR Model and Soft Sensing Application","display_name":"Mixture Bayesian Regularization of PCR Model and Soft Sensing Application","publication_year":2014,"publication_date":"2014-12-22","ids":{"openalex":"https://openalex.org/W2018411202","doi":"https://doi.org/10.1109/tie.2014.2385042","mag":"2018411202"},"language":"en","primary_location":{"id":"doi:10.1109/tie.2014.2385042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2014.2385042","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Electronics","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/A5067726465","display_name":"Zhiqiang Ge","orcid":"https://orcid.org/0000-0002-2071-4380"},"institutions":[{"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":true,"raw_author_name":"Zhiqiang Ge","raw_affiliation_strings":["State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou, China","Department of Control Science & Engineering, Zhejiang University, Hangzhou, CHINA"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4391767838"]},{"raw_affiliation_string":"Department of Control Science & Engineering, Zhejiang University, Hangzhou, CHINA","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5067726465"],"corresponding_institution_ids":["https://openalex.org/I4391767838","https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":2.8718,"has_fulltext":false,"cited_by_count":65,"citation_normalized_percentile":{"value":0.90940804,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"62","issue":"7","first_page":"4336","last_page":"4343"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9998999834060669,"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":0.9998999834060669,"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/T10791","display_name":"Advanced Control Systems Optimization","score":0.9898999929428101,"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9854999780654907,"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/hyperparameter","display_name":"Hyperparameter","score":0.7500005960464478},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.7173449993133545},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5893339514732361},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5842308402061462},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5707741379737854},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5623635649681091},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5613529086112976},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5327733755111694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5107593536376953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4967859387397766},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4944472312927246},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.4314126968383789},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4134272038936615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36430126428604126},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3593147397041321},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23139110207557678},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.06674438714981079}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.7500005960464478},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.7173449993133545},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5893339514732361},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5842308402061462},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5707741379737854},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5623635649681091},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5613529086112976},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5327733755111694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5107593536376953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4967859387397766},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4944472312927246},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4314126968383789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4134272038936615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36430126428604126},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3593147397041321},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23139110207557678},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.06674438714981079}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tie.2014.2385042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2014.2385042","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":27,"referenced_works":["https://openalex.org/W201467409","https://openalex.org/W563702179","https://openalex.org/W1663973292","https://openalex.org/W1965875070","https://openalex.org/W1966863755","https://openalex.org/W1984672166","https://openalex.org/W1998023709","https://openalex.org/W1999377952","https://openalex.org/W2000651380","https://openalex.org/W2005051528","https://openalex.org/W2036887017","https://openalex.org/W2058139389","https://openalex.org/W2074058676","https://openalex.org/W2079692514","https://openalex.org/W2084408974","https://openalex.org/W2094298886","https://openalex.org/W2097543469","https://openalex.org/W2103731208","https://openalex.org/W2105459947","https://openalex.org/W2130086376","https://openalex.org/W2133622633","https://openalex.org/W2140336071","https://openalex.org/W2155469951","https://openalex.org/W2322097696","https://openalex.org/W2464276105","https://openalex.org/W2493627968","https://openalex.org/W4212863985"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W84255947","https://openalex.org/W2153481672","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2061347451","https://openalex.org/W1505865477"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,72],"Bayesian":[4,75,102,136],"regularization":[5,76,103,137],"mechanism":[6],"is":[7,34,78,91],"provided":[8],"for":[9,36,93,112],"automatically":[10],"determining":[11],"the":[12,18,27,31,37,44,52,65,69,83,94,113,122,134,139],"number":[13],"of":[14,39,54,68,85,97,116,124],"latent":[15,41,56,86],"variables":[16,42,118],"in":[17,43,119,147],"probabilistic":[19,106],"principal":[20],"component":[21],"regression":[22],"(PPCR)":[23],"model.":[24,46],"Different":[25],"from":[26],"unsupervised":[28],"principal-component-analysis":[29],"model,":[30,71,138],"response":[32],"variable":[33,57],"incorporated":[35],"supervision":[38],"selecting":[40],"PPCR":[45,70],"By":[47],"introducing":[48],"two":[49,129],"hyperparameter":[50],"vectors,":[51],"effectiveness":[53],"each":[55],"can":[58],"be":[59],"well":[60],"measured":[61],"and":[62,100,149],"controlled.":[63],"For":[64],"mixture":[66,74,101,140],"form":[67],"corresponding":[73],"strategy":[77],"further":[79],"developed":[80,111],"to":[81,133],"control":[82],"dimensionality":[84],"variables.":[87],"The":[88],"expectation-maximization":[89],"algorithm":[90],"employed":[92],"parameter":[95],"learning":[96],"both":[98],"single":[99,135],"models.":[104],"Two":[105],"soft":[107,144],"sensors":[108],"are":[109,126],"then":[110],"online":[114],"estimation":[115],"key":[117],"industrial":[120],"processes,":[121],"performances":[123],"which":[125],"evaluated":[127],"through":[128],"case":[130],"studies.":[131],"Compared":[132],"model":[141],"shows":[142],"stronger":[143],"sensing":[145],"abilities":[146],"nonlinear":[148],"multimode":[150],"processes.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
