{"id":"https://openalex.org/W4410583210","doi":"https://doi.org/10.1109/tnnls.2025.3567757","title":"Factorization-Based Broad Learning System With Time-Dependent Structure","display_name":"Factorization-Based Broad Learning System With Time-Dependent Structure","publication_year":2025,"publication_date":"2025-05-21","ids":{"openalex":"https://openalex.org/W4410583210","doi":"https://doi.org/10.1109/tnnls.2025.3567757","pmid":"https://pubmed.ncbi.nlm.nih.gov/40397642"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3567757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3567757","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/A5066316185","display_name":"Chen Li","orcid":"https://orcid.org/0000-0003-2839-9335"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Li","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2839-9335","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049730248","display_name":"Zeyi Liu","orcid":"https://orcid.org/0000-0003-2177-8906"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeyi Liu","raw_affiliation_strings":["Shanghai BYD Company Ltd., Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-2177-8906","affiliations":[{"raw_affiliation_string":"Shanghai BYD Company Ltd., Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038690943","display_name":"Xiao He","orcid":"https://orcid.org/0000-0002-4588-0887"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao He","raw_affiliation_strings":["Shanghai BYD Company Ltd., Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4588-0887","affiliations":[{"raw_affiliation_string":"Shanghai BYD Company Ltd., Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025795829","display_name":"Pengyu Han","orcid":"https://orcid.org/0009-0003-2942-0631"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pengyu Han","raw_affiliation_strings":["Shanghai BYD Company Ltd., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai BYD Company Ltd., Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5066316185"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04935846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"9","first_page":"17227","last_page":"17238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9616000056266785,"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":0.9616000056266785,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.6597413420677185},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5370160341262817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38265135884284973},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19183120131492615}],"concepts":[{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.6597413420677185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5370160341262817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38265135884284973},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19183120131492615}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3567757","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3567757","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:40397642","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40397642","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/G3615321702","display_name":null,"funder_award_id":"624B2087","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6228484772","display_name":null,"funder_award_id":"62473223","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":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1506342804","https://openalex.org/W1520511539","https://openalex.org/W1996640396","https://openalex.org/W2020804487","https://openalex.org/W2123223828","https://openalex.org/W2134603844","https://openalex.org/W2158054309","https://openalex.org/W2159579247","https://openalex.org/W2539298695","https://openalex.org/W2626498001","https://openalex.org/W2738226240","https://openalex.org/W2887576641","https://openalex.org/W3003134479","https://openalex.org/W3012555737","https://openalex.org/W3085372223","https://openalex.org/W3094071795","https://openalex.org/W3115913152","https://openalex.org/W3193978175","https://openalex.org/W4200597037","https://openalex.org/W4226198717","https://openalex.org/W4240893730","https://openalex.org/W4240959780","https://openalex.org/W4285507498","https://openalex.org/W4310077797","https://openalex.org/W4312258136","https://openalex.org/W4320800818","https://openalex.org/W4360770771","https://openalex.org/W4366238713","https://openalex.org/W4366377783","https://openalex.org/W4366378396","https://openalex.org/W4385627271","https://openalex.org/W4388207980","https://openalex.org/W4388520280","https://openalex.org/W4389331447","https://openalex.org/W4389584681","https://openalex.org/W4390340795","https://openalex.org/W4390357683","https://openalex.org/W4390616135","https://openalex.org/W4390706846","https://openalex.org/W4391305696","https://openalex.org/W4393991907","https://openalex.org/W4394834020","https://openalex.org/W4397026374","https://openalex.org/W4400033563","https://openalex.org/W4400100344","https://openalex.org/W4400100364","https://openalex.org/W4404310025","https://openalex.org/W4404316897"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,145],"response":[1],"to":[2,72,155,218],"the":[3,22,39,85,96,106,111,140,152,195],"increasing":[4,159],"complexity":[5],"of":[6,24,65,88,102,108,189,200],"tasks":[7,52],"in":[8,46,53,162,180,227],"artificial":[9],"intelligence,":[10],"broad":[11],"learning":[12,138],"systems":[13],"(BLSs)":[14],"have":[15],"emerged":[16],"as":[17,29,73],"essential":[18],"tools,":[19],"especially":[20],"given":[21],"limitations":[23],"deep":[25],"neural":[26],"networks,":[27],"such":[28],"their":[30],"extensive":[31],"training":[32],"and":[33,42,178,184,191,197,209,221],"computational":[34,40,198],"demands.":[35],"This":[36,82],"study":[37],"addresses":[38,215],"inefficiencies":[41],"numerical":[43,80,167,219],"instabilities":[44],"inherent":[45],"traditional":[47,86,173],"BLS":[48,66,112],"when":[49,117],"handling":[50,181],"complex":[51],"dynamic":[54,125,163,210],"environments.":[55,164],"To":[56],"mitigate":[57],"these":[58],"challenges,":[59],"we":[60],"propose":[61],"an":[62],"enhanced":[63],"version":[64],"incorporating":[67],"QR":[68],"factorization":[69],"(QRF),":[70],"referred":[71],"QRBLS,":[74],"which":[75,92],"is":[76,105],"known":[77],"for":[78,142,206],"improving":[79,115],"stability.":[81],"framework":[83],"replaces":[84],"method":[87],"computing":[89],"output":[90],"weights,":[91],"typically":[93],"relies":[94],"on":[95],"Moore-Penrose":[97],"pseudoinverse.":[98],"The":[99,187],"primary":[100],"contribution":[101],"this":[103],"article":[104],"integration":[107,188],"QRF":[109,190],"into":[110],"architecture,":[113],"thereby":[114],"stability":[116,177],"processing":[118],"large-scale":[119],"datasets.":[120],"QRBLS":[121,171,213],"also":[122],"features":[123],"a":[124,147,203],"updating":[126],"mechanism":[127],"that":[128,170],"adjusts":[129],"model":[130],"parameters":[131],"efficiently":[132],"with":[133],"new":[134],"data,":[135],"enabling":[136],"continuous":[137,222],"without":[139],"need":[141],"full-model":[143],"re-evaluation.":[144],"addition,":[146],"time-dependent":[148],"structure":[149],"(TDS)":[150],"enhances":[151],"model's":[153],"responsiveness":[154],"temporal":[156],"data":[157,182],"changes,":[158],"its":[160],"utility":[161],"Validation":[165],"through":[166],"experiments":[168],"demonstrated":[169],"outperformed":[172],"BLS,":[174,201],"exhibiting":[175],"superior":[176],"adaptability":[179,196],"anomalies":[183],"rapid":[185],"updates.":[186],"TDS":[192],"significantly":[193],"improves":[194],"efficiency":[199],"providing":[202],"robust":[204],"solution":[205],"large":[207],"scale":[208],"AI":[211],"applications.":[212],"effectively":[214],"challenges":[216],"related":[217],"instability":[220],"learning,":[223],"offering":[224],"practical":[225],"improvements":[226],"real-world":[228],"settings.":[229]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}