{"id":"https://openalex.org/W3001640719","doi":"https://doi.org/10.3390/s20030695","title":"Robust Soft Sensor with Deep Kernel Learning for Quality Prediction in Rubber Mixing Processes","display_name":"Robust Soft Sensor with Deep Kernel Learning for Quality Prediction in Rubber Mixing Processes","publication_year":2020,"publication_date":"2020-01-27","ids":{"openalex":"https://openalex.org/W3001640719","doi":"https://doi.org/10.3390/s20030695","mag":"3001640719","pmid":"https://pubmed.ncbi.nlm.nih.gov/32012753"},"language":"en","primary_location":{"id":"doi:10.3390/s20030695","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20030695","pdf_url":"https://www.mdpi.com/1424-8220/20/3/695/pdf?version=1581059706","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/3/695/pdf?version=1581059706","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082329078","display_name":"Shuihua Zheng","orcid":"https://orcid.org/0000-0002-7112-2940"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuihua Zheng","raw_affiliation_strings":["Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100674710","display_name":"Kaixin Liu","orcid":"https://orcid.org/0000-0001-5573-1781"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaixin Liu","raw_affiliation_strings":["Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068133635","display_name":"Yili Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102827","display_name":"Shanghai Customs College","ror":"https://ror.org/01agvej60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210102827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yili Xu","raw_affiliation_strings":["Shanghai Customs, Shanghai 200120, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Customs, Shanghai 200120, China","institution_ids":["https://openalex.org/I4210102827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353558","display_name":"Hao Chen","orcid":"https://orcid.org/0000-0002-4883-5168"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210151023","display_name":"Quanzhou Institute of Equipment Manufacturing Haixi Institute","ror":"https://ror.org/05ev3vr27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Chen","raw_affiliation_strings":["Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang 362200, China"],"affiliations":[{"raw_affiliation_string":"Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang 362200, China","institution_ids":["https://openalex.org/I4210151023","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100723921","display_name":"Xuelei Zhang","orcid":"https://orcid.org/0000-0001-5811-4412"},"institutions":[{"id":"https://openalex.org/I4210102827","display_name":"Shanghai Customs College","ror":"https://ror.org/01agvej60","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210102827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelei Zhang","raw_affiliation_strings":["Shanghai Customs, Shanghai 200120, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Customs, Shanghai 200120, China","institution_ids":["https://openalex.org/I4210102827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100739893","display_name":"Yi Liu","orcid":"https://orcid.org/0000-0002-4066-689X"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Liu","raw_affiliation_strings":["Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100739893"],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":2.8197,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.90320864,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"20","issue":"3","first_page":"695","last_page":"695"},"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/T11472","display_name":"Analytical Chemistry and Sensors","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1502","display_name":"Bioengineering"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9732000231742859,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7003883123397827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6604560017585754},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6148471236228943},{"id":"https://openalex.org/keywords/soft-sensor","display_name":"Soft sensor","score":0.6061369776725769},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.574099600315094},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5369268655776978},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.49959588050842285},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48234790563583374},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.46557706594467163},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4525458514690399},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4350903332233429},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42310184240341187},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3684982657432556},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1389666199684143},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.10303783416748047},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10093674063682556}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7003883123397827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6604560017585754},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6148471236228943},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.6061369776725769},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.574099600315094},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5369268655776978},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.49959588050842285},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48234790563583374},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.46557706594467163},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4525458514690399},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4350903332233429},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42310184240341187},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3684982657432556},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1389666199684143},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.10303783416748047},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10093674063682556},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s20030695","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20030695","pdf_url":"https://www.mdpi.com/1424-8220/20/3/695/pdf?version=1581059706","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:32012753","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32012753","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:e5c9307029e74f47bc20d13d780f171e","is_oa":true,"landing_page_url":"https://doaj.org/article/e5c9307029e74f47bc20d13d780f171e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 3, p 695 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/3/695/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s20030695","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7038447","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7038447","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20030695","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20030695","pdf_url":"https://www.mdpi.com/1424-8220/20/3/695/pdf?version=1581059706","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G3840691741","display_name":null,"funder_award_id":"61873241, 51476144, and 61603369","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3001640719.pdf","grobid_xml":"https://content.openalex.org/works/W3001640719.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W44815768","https://openalex.org/W1547485964","https://openalex.org/W1980697376","https://openalex.org/W1987763041","https://openalex.org/W1996139334","https://openalex.org/W2000651380","https://openalex.org/W2022176164","https://openalex.org/W2032078553","https://openalex.org/W2032355746","https://openalex.org/W2040726420","https://openalex.org/W2100128988","https://openalex.org/W2133393721","https://openalex.org/W2135160607","https://openalex.org/W2138728394","https://openalex.org/W2144097240","https://openalex.org/W2165819448","https://openalex.org/W2316011343","https://openalex.org/W2338807552","https://openalex.org/W2396958038","https://openalex.org/W2410531948","https://openalex.org/W2516713989","https://openalex.org/W2606776959","https://openalex.org/W2683785459","https://openalex.org/W2737248315","https://openalex.org/W2759373267","https://openalex.org/W2766725700","https://openalex.org/W2789440825","https://openalex.org/W2810016643","https://openalex.org/W2895250764","https://openalex.org/W2903712458","https://openalex.org/W2904067769","https://openalex.org/W2919115771","https://openalex.org/W2919235887","https://openalex.org/W2965420085","https://openalex.org/W2981522341","https://openalex.org/W2995527107","https://openalex.org/W2998320282","https://openalex.org/W6601785968"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W4389249638","https://openalex.org/W2733410219","https://openalex.org/W2734358244","https://openalex.org/W4388700941"],"abstract_inverted_index":{"Although":[0],"several":[1],"data-driven":[2],"soft":[3,27,55],"sensors":[4],"are":[5,100,118],"available,":[6],"online":[7],"reliable":[8,115],"prediction":[9,116],"of":[10,98,111,129],"the":[11,40,80,83,87,95,103,109,125],"Mooney":[12,88],"viscosity":[13,89],"in":[14],"industrial":[15,122],"rubber":[16],"mixing":[17],"processes":[18],"is":[19,36,76],"still":[20],"a":[21,53,72],"challenging":[22],"task.":[23],"A":[24],"robust":[25,105],"semi-supervised":[26],"sensor,":[28],"called":[29],"ensemble":[30,41,112],"deep":[31,43],"correntropy":[32,48],"kernel":[33,49],"regression":[34,50],"(EDCKR),":[35],"proposed.":[37],"It":[38],"integrates":[39],"strategy,":[42,113],"brief":[44],"network":[45],"(DBN),":[46],"and":[47,86,127],"(CKR)":[51],"into":[52],"unified":[54],"sensing":[56],"framework.":[57],"The":[58],"multilevel":[59],"DBN-based":[60],"unsupervised":[61],"learning":[62],"stage":[63],"extracts":[64],"useful":[65],"information":[66],"from":[67],"all":[68],"secondary":[69],"variables.":[70],"Sequentially,":[71],"supervised":[73],"CKR":[74],"model":[75],"built":[77],"to":[78],"explore":[79],"relationship":[81],"between":[82],"extracted":[84],"features":[85],"values.":[90],"Without":[91],"cumbersome":[92],"preprocessing":[93],"steps,":[94],"negative":[96],"effects":[97],"outliers":[99],"reduced":[101],"using":[102],"CKR-based":[104],"nonlinear":[106],"estimator.":[107],"With":[108],"help":[110],"more":[114],"results":[117],"further":[119],"obtained.":[120],"An":[121],"case":[123],"validates":[124],"practicality":[126],"reliability":[128],"EDCKR.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
