{"id":"https://openalex.org/W4397026374","doi":"https://doi.org/10.1109/tnnls.2024.3396659","title":"Robust Incremental Broad Learning System for Data Streams of Uncertain Scale","display_name":"Robust Incremental Broad Learning System for Data Streams of Uncertain Scale","publication_year":2024,"publication_date":"2024-05-17","ids":{"openalex":"https://openalex.org/W4397026374","doi":"https://doi.org/10.1109/tnnls.2024.3396659","pmid":"https://pubmed.ncbi.nlm.nih.gov/38758620"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3396659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3396659","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5098683521","display_name":"Linjun Zhong","orcid":"https://orcid.org/0009-0004-0224-6108"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linjun Zhong","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","Pazhou Laboratory, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Pazhou Laboratory, Guangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100643265","display_name":"C. L. Philip Chen","orcid":"https://orcid.org/0000-0001-5451-7230"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"C. L. Philip Chen","raw_affiliation_strings":["School of Computer Science and Engineering and the Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information, South China University of Technology, Guangzhou, China","Engineering Research Center, Ministry of Education on Health Intelligent Perception and Parallel Digital Human, Guangzhou, China","Brain and Affective Cognitive Research Center, Pazhou Laboratory, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and the Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Engineering Research Center, Ministry of Education on Health Intelligent Perception and Parallel Digital Human, Guangzhou, China","institution_ids":["https://openalex.org/I1327237609"]},{"raw_affiliation_string":"Brain and Affective Cognitive Research Center, Pazhou Laboratory, Guangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024136480","display_name":"Jifeng Guo","orcid":"https://orcid.org/0000-0002-8520-3178"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jifeng Guo","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","Pazhou Laboratory, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Pazhou Laboratory, Guangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100378800","display_name":"Tong Zhang","orcid":"https://orcid.org/0000-0002-7025-6365"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Zhang","raw_affiliation_strings":["School of Computer Science and Engineering and the Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information, South China University of Technology, Guangzhou, China","Engineering Research Center, Ministry of Education on Health Intelligent Perception and Parallel Digital Human, Guangzhou, China","Brain and Affective Cognitive Research Center, Pazhou Laboratory, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and the Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Engineering Research Center, Ministry of Education on Health Intelligent Perception and Parallel Digital Human, Guangzhou, China","institution_ids":["https://openalex.org/I1327237609"]},{"raw_affiliation_string":"Brain and Affective Cognitive Research Center, Pazhou Laboratory, Guangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5098683521"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":3.7565,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.93842262,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"36","issue":"4","first_page":"7580","last_page":"7593"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9988999962806702,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9677000045776367,"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/T10057","display_name":"Face and Expression Recognition","score":0.9607999920845032,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.7008416056632996},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.614946722984314},{"id":"https://openalex.org/keywords/ridge","display_name":"Ridge","score":0.5428344011306763},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5355555415153503},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5198967456817627},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49596843123435974},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48370295763015747},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4469625949859619},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42042043805122375},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.410073459148407},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40599969029426575},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33890485763549805},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20407378673553467},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11169588565826416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7008416056632996},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.614946722984314},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.5428344011306763},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5355555415153503},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5198967456817627},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49596843123435974},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48370295763015747},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4469625949859619},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42042043805122375},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.410073459148407},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40599969029426575},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33890485763549805},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20407378673553467},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11169588565826416},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3396659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3396659","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38758620","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38758620","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1487701234","display_name":null,"funder_award_id":"62222603","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2021969373","display_name":null,"funder_award_id":"92267203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3556693586","display_name":null,"funder_award_id":"2021ZD0200700","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"},{"id":"https://openalex.org/G5197980865","display_name":null,"funder_award_id":"2019YFA0706200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5198162578","display_name":null,"funder_award_id":"62076102","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"},{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1154478554","https://openalex.org/W2003912160","https://openalex.org/W2012638612","https://openalex.org/W2026131661","https://openalex.org/W2037727941","https://openalex.org/W2110485445","https://openalex.org/W2111072639","https://openalex.org/W2112796928","https://openalex.org/W2134557905","https://openalex.org/W2514029627","https://openalex.org/W2734358244","https://openalex.org/W2738226240","https://openalex.org/W2742229469","https://openalex.org/W2884282566","https://openalex.org/W2890126432","https://openalex.org/W2905036448","https://openalex.org/W2910673030","https://openalex.org/W2954929116","https://openalex.org/W2962696932","https://openalex.org/W2966501701","https://openalex.org/W3007551217","https://openalex.org/W3008112497","https://openalex.org/W3018523095","https://openalex.org/W3033811744","https://openalex.org/W3115913152","https://openalex.org/W3119535973","https://openalex.org/W3127715955","https://openalex.org/W3135693966","https://openalex.org/W3136378322","https://openalex.org/W3138794164","https://openalex.org/W3150749950","https://openalex.org/W3159459366","https://openalex.org/W3168997536","https://openalex.org/W3197030567","https://openalex.org/W3198841289","https://openalex.org/W3205506449","https://openalex.org/W4210847455","https://openalex.org/W4226269423","https://openalex.org/W4285507498","https://openalex.org/W4294068568","https://openalex.org/W4308744813","https://openalex.org/W4310299220","https://openalex.org/W4361801575","https://openalex.org/W4384197213","https://openalex.org/W4384521532","https://openalex.org/W4387303368","https://openalex.org/W4390357683","https://openalex.org/W4390706846","https://openalex.org/W4391341341","https://openalex.org/W6734065873","https://openalex.org/W6743688258","https://openalex.org/W6774521142","https://openalex.org/W6774666825"],"related_works":["https://openalex.org/W4242029529","https://openalex.org/W2361826657","https://openalex.org/W2389214306","https://openalex.org/W2369419402","https://openalex.org/W2966404314","https://openalex.org/W2965083567","https://openalex.org/W3148196241","https://openalex.org/W1977912248","https://openalex.org/W3092773549","https://openalex.org/W2122926592"],"abstract_inverted_index":{"Due":[0],"to":[1,42,75,144,195],"its":[2,21,53,140],"marvelous":[3],"performance":[4],"and":[5,28,51,102,122,164,181],"remarkable":[6],"scalability,":[7],"a":[8,15,56],"broad":[9],"learning":[10,23],"system":[11],"(BLS)":[12],"has":[13],"aroused":[14],"wide":[16],"range":[17],"of":[18,84,147],"attention.":[19],"However,":[20],"incremental":[22,58,95,128,138,154,175],"suffers":[24],"from":[25,131],"low":[26],"accuracy":[27],"long":[29],"training":[30],"time,":[31],"especially":[32],"when":[33,177],"dealing":[34],"with":[35,126,151],"unstable":[36,182],"data":[37,183],"streams,":[38],"making":[39],"it":[40],"difficult":[41],"apply":[43],"in":[44,90,118,135],"real-world":[45],"scenarios.":[46],"To":[47],"overcome":[48],"these":[49],"issues":[50],"enrich":[52],"relevant":[54],"research,":[55],"robust":[57],"BLS":[59],"(RI-BLS)":[60],"is":[61,87,115],"proposed.":[62],"In":[63,110],"this":[64,112],"method,":[65],"the":[66,77,81,136,145,152,156,189],"proposed":[67,157,190],"weight":[68,191],"update":[69,113,192],"strategy":[70,114,193],"introduces":[71],"two":[72,99],"memory":[73,100],"matrices":[74,101],"store":[76],"learned":[78],"information,":[79],"thus":[80],"computational":[82],"procedure":[83],"ridge":[85,92,107],"regression":[86,108],"decomposed,":[88],"resulting":[89],"precomputed":[91,106],"regression.":[93],"During":[94],"learning,":[96],"RI-BLS":[97,172],"updates":[98],"renews":[103],"weights":[104],"via":[105],"efficiently.":[109],"addition,":[111],"theoretically":[116],"analyzed":[117],"error,":[119],"time":[120,162],"complexity,":[121],"space":[123,166],"complexity":[124,163],"compared":[125],"existing":[127,153],"BLSs.":[129],"Different":[130],"Greville's":[132],"method":[133,158],"used":[134],"original":[137],"BLS,":[139],"results":[141],"are":[142],"closer":[143],"solution":[146],"one-shot":[148],"calculation.":[149],"Compared":[150],"BLSs,":[155],"exhibits":[159],"more":[160],"stable":[161,180],"superior":[165],"complexity.":[167],"The":[168],"experiments":[169,186],"prove":[170],"that":[171,188],"outperforms":[173],"other":[174,196],"BLSs":[176],"handling":[178],"both":[179],"streams.":[184],"Furthermore,":[185],"demonstrate":[187],"applies":[194],"random":[197],"neural":[198],"networks":[199],"as":[200],"well.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}