{"id":"https://openalex.org/W4318953536","doi":"https://doi.org/10.1109/tcyb.2023.3235155","title":"Adaptive Multioutput Gradient RBF Tracker for Nonlinear and Nonstationary Regression","display_name":"Adaptive Multioutput Gradient RBF Tracker for Nonlinear and Nonstationary Regression","publication_year":2023,"publication_date":"2023-02-02","ids":{"openalex":"https://openalex.org/W4318953536","doi":"https://doi.org/10.1109/tcyb.2023.3235155","pmid":"https://pubmed.ncbi.nlm.nih.gov/37022387"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2023.3235155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2023.3235155","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":null,"license_id":null,"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":"green","oa_url":"https://eprints.whiterose.ac.uk/194834/1/Adaptive_Multi_Output_Gradient_RBF_Tracker_For_Nonlinear_and_Nonstationary_Regression__4_.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007020277","display_name":"Tong Liu","orcid":"https://orcid.org/0000-0001-6449-0625"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tong Liu","raw_affiliation_strings":["Department of Chemical Engineering, Imperial College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0001-6449-0625","affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320969","display_name":"Sheng Chen","orcid":"https://orcid.org/0000-0001-6882-600X"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]},{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Sheng Chen","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton, Southampton, U.K","Faculty of Information Science and Engineering, Ocean University of China, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0001-6882-600X","affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton, Southampton, U.K","institution_ids":["https://openalex.org/I43439940"]},{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456957","display_name":"Kang Li","orcid":"https://orcid.org/0000-0001-6657-0522"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kang Li","raw_affiliation_strings":["School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0001-6657-0522","affiliations":[{"raw_affiliation_string":"School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036597286","display_name":"Shaojun Gan","orcid":"https://orcid.org/0000-0002-7445-8386"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaojun Gan","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7445-8386","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067133312","display_name":"C.J. Harris","orcid":"https://orcid.org/0000-0002-8504-9043"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chris J. Harris","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton, Southampton, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8504-9043","affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton, Southampton, U.K","institution_ids":["https://openalex.org/I43439940"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1078,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.9158574,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"53","issue":"12","first_page":"7906","last_page":"7919"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9983999729156494,"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/T11236","display_name":"Control Systems and Identification","score":0.9945999979972839,"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/nonlinear-system","display_name":"Nonlinear system","score":0.5981068015098572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5801137089729309},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5763871073722839},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48405924439430237},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.4729993939399719},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4549919068813324},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45479467511177063},{"id":"https://openalex.org/keywords/nonlinear-regression","display_name":"Nonlinear regression","score":0.43774840235710144},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4346705675125122},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4332003593444824},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4126799404621124},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3962123692035675},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.3563641905784607},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25313353538513184},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24331432580947876},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1820271611213684},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.1552431285381317},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09327366948127747}],"concepts":[{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5981068015098572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5801137089729309},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5763871073722839},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48405924439430237},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.4729993939399719},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4549919068813324},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45479467511177063},{"id":"https://openalex.org/C46889948","wikidata":"https://www.wikidata.org/wiki/Q2755024","display_name":"Nonlinear regression","level":3,"score":0.43774840235710144},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4346705675125122},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4332003593444824},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4126799404621124},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3962123692035675},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3563641905784607},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25313353538513184},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24331432580947876},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1820271611213684},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.1552431285381317},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09327366948127747},{"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/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tcyb.2023.3235155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2023.3235155","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:37022387","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37022387","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},{"id":"pmh:oai:eprints.soton.ac.uk:474173","is_oa":false,"landing_page_url":"https://eprints.soton.ac.uk/474173/2/Adaptive_Multioutput_Gradient_RBF_Tracker_for_Nonlinear_and_Nonstationary_Regression.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401020","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:194834","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-6657-0522>","pdf_url":"https://eprints.whiterose.ac.uk/194834/1/Adaptive_Multi_Output_Gradient_RBF_Tracker_For_Nonlinear_and_Nonstationary_Regression__4_.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:eprints.whiterose.ac.uk:194834","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-6657-0522>","pdf_url":"https://eprints.whiterose.ac.uk/194834/1/Adaptive_Multi_Output_Gradient_RBF_Tracker_For_Nonlinear_and_Nonstationary_Regression__4_.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7824591592","display_name":null,"funder_award_id":"62003011","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4318953536.pdf","grobid_xml":"https://content.openalex.org/works/W4318953536.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W623776627","https://openalex.org/W1495274654","https://openalex.org/W1522301498","https://openalex.org/W1596717185","https://openalex.org/W1904826605","https://openalex.org/W1962266374","https://openalex.org/W1968018278","https://openalex.org/W1973268799","https://openalex.org/W1995417155","https://openalex.org/W2017413629","https://openalex.org/W2020207716","https://openalex.org/W2036455044","https://openalex.org/W2039617872","https://openalex.org/W2047282638","https://openalex.org/W2064675550","https://openalex.org/W2100495367","https://openalex.org/W2102380305","https://openalex.org/W2114865067","https://openalex.org/W2121129397","https://openalex.org/W2121854064","https://openalex.org/W2122347864","https://openalex.org/W2122496631","https://openalex.org/W2131246644","https://openalex.org/W2132320458","https://openalex.org/W2135350367","https://openalex.org/W2137442237","https://openalex.org/W2152949102","https://openalex.org/W2155399784","https://openalex.org/W2158054309","https://openalex.org/W2344849981","https://openalex.org/W2363497421","https://openalex.org/W2424068677","https://openalex.org/W2539756354","https://openalex.org/W2885060605","https://openalex.org/W2890137519","https://openalex.org/W2895264248","https://openalex.org/W2897657100","https://openalex.org/W2920714358","https://openalex.org/W2929291387","https://openalex.org/W2962264430","https://openalex.org/W2969227524","https://openalex.org/W2980999096","https://openalex.org/W2982857584","https://openalex.org/W3010725993","https://openalex.org/W3016388251","https://openalex.org/W3021303430","https://openalex.org/W3022392400","https://openalex.org/W3048905650","https://openalex.org/W3081318531","https://openalex.org/W3092219863","https://openalex.org/W3092486253","https://openalex.org/W3095326391","https://openalex.org/W3118157880","https://openalex.org/W3208352000","https://openalex.org/W6631190155","https://openalex.org/W6637611448","https://openalex.org/W7058139890"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"Multioutput":[0],"regression":[1,126],"of":[2,32,135],"nonlinear":[3,34],"and":[4,14,35,98,139],"nonstationary":[5,36],"data":[6],"is":[7,43,71],"largely":[8],"understudied":[9],"in":[10,62,133],"both":[11],"machine":[12],"learning":[13],"control":[15],"communities.":[16],"This":[17],"article":[18],"develops":[19],"an":[20,66],"adaptive":[21,67,136],"multioutput":[22,33,104,125],"gradient":[23],"radial":[24],"basis":[25],"function":[26],"(MGRBF)":[27],"tracker":[28,70,119],"for":[29,106],"online":[30,79,124,140],"modeling":[31,137],"processes.":[37],"Specifically,":[38],"a":[39,47,87,101],"compact":[40],"MGRBF":[41,68,76],"network":[42,77],"first":[44],"constructed":[45],"with":[46,86],"new":[48,88],"two-step":[49],"training":[50],"procedure":[51],"to":[52],"produce":[53],"excellent":[54],"predictive":[55],"capacity.":[56],"To":[57],"improve":[58],"its":[59],"tracking":[60],"ability":[61],"fast":[63],"time-varying":[64],"scenarios,":[65],"(AMGRBF)":[69],"proposed,":[72],"which":[73],"updates":[74],"the":[75,82,93,107,116],"structure":[78],"by":[80],"replacing":[81],"worst":[83],"performing":[84],"node":[85,89],"that":[90,115],"automatically":[91],"encodes":[92],"newly":[94],"emerging":[95],"system":[96,109],"state":[97],"acts":[99],"as":[100,128,130],"perfect":[102],"local":[103],"predictor":[105],"current":[108],"state.":[110],"Extensive":[111],"experimental":[112],"results":[113],"confirm":[114],"proposed":[117],"AMGRBF":[118],"significantly":[120],"outperforms":[121],"existing":[122],"state-of-the-art":[123],"methods":[127],"well":[129],"deep-learning-based":[131],"models,":[132],"terms":[134],"accuracy":[138],"computational":[141],"complexity.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}