{"id":"https://openalex.org/W2137820384","doi":"https://doi.org/10.1109/fuzz.2001.1008912","title":"Efficient training algorithm for Takagi-Sugeno type neuro-fuzzy network","display_name":"Efficient training algorithm for Takagi-Sugeno type neuro-fuzzy network","publication_year":2002,"publication_date":"2002-11-14","ids":{"openalex":"https://openalex.org/W2137820384","doi":"https://doi.org/10.1109/fuzz.2001.1008912","mag":"2137820384"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz.2001.1008912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz.2001.1008912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)","raw_type":"proceedings-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/A5061761320","display_name":"A.K. Palit","orcid":"https://orcid.org/0009-0007-7444-2994"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"A.K. Palit","raw_affiliation_strings":["ITS/Control Engineering Laboratory, Delft University of Technnology, Delft, Netherlands","Repas-AEG Information Technologies GmbH, Bremen, Germany"],"affiliations":[{"raw_affiliation_string":"ITS/Control Engineering Laboratory, Delft University of Technnology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]},{"raw_affiliation_string":"Repas-AEG Information Technologies GmbH, Bremen, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084264842","display_name":"Robert Babu\u0161ka","orcid":"https://orcid.org/0000-0001-9578-8598"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"R. Babuska","raw_affiliation_strings":["ITS / Control Engineering Laboratory, Delft University of Technnology, Delft, Netherlands"],"affiliations":[{"raw_affiliation_string":"ITS / Control Engineering Laboratory, Delft University of Technnology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5061761320"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":1.6675,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.86435528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2","issue":null,"first_page":"1367","last_page":"1371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9998000264167786,"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/T10320","display_name":"Neural Networks and Applications","score":0.9998000264167786,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9973000288009644,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/jacobian-matrix-and-determinant","display_name":"Jacobian matrix and determinant","score":0.7776191234588623},{"id":"https://openalex.org/keywords/transpose","display_name":"Transpose","score":0.7231951355934143},{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.6438472867012024},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.6277689337730408},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6238664388656616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5746703147888184},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4915977418422699},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4841071367263794},{"id":"https://openalex.org/keywords/levenberg\u2013marquardt-algorithm","display_name":"Levenberg\u2013Marquardt algorithm","score":0.4580288529396057},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.45748865604400635},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.42479386925697327},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31087151169776917},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2800261378288269},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.09548437595367432},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.09421911835670471}],"concepts":[{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.7776191234588623},{"id":"https://openalex.org/C200106649","wikidata":"https://www.wikidata.org/wiki/Q223683","display_name":"Transpose","level":3,"score":0.7231951355934143},{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.6438472867012024},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.6277689337730408},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6238664388656616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5746703147888184},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4915977418422699},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4841071367263794},{"id":"https://openalex.org/C87578567","wikidata":"https://www.wikidata.org/wiki/Q1426494","display_name":"Levenberg\u2013Marquardt algorithm","level":3,"score":0.4580288529396057},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.45748865604400635},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.42479386925697327},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31087151169776917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2800261378288269},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.09548437595367432},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.09421911835670471},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz.2001.1008912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz.2001.1008912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1548649525","https://openalex.org/W1824237966","https://openalex.org/W2145479133","https://openalex.org/W2155482699"],"related_works":["https://openalex.org/W2263948369","https://openalex.org/W2350095335","https://openalex.org/W2016247732","https://openalex.org/W2544528198","https://openalex.org/W2131949474","https://openalex.org/W2396307289","https://openalex.org/W2405649773","https://openalex.org/W2327154875","https://openalex.org/W2133391116","https://openalex.org/W3048650638"],"abstract_inverted_index":{"The":[0,19,60,97],"paper":[1],"describes":[2],"an":[3],"algorithm":[4,21,58,63,74,99,191],"that":[5,28,54,112,157],"can":[6,30],"be":[7,161],"used":[8],"to":[9,46,106,131,160,174],"train":[10],"the":[11,26,32,36,40,47,55,71,80,90,95,101,108,114,134,148,151,164,178,182,188],"Takagi-Sugeno":[12],"(TS)":[13],"type":[14],"neuro-fuzzy":[15,185,195],"network":[16],"very":[17,23],"efficiently.":[18],"training":[20,62,73,183,190],"is":[22,64,113,155,158,192],"efficient":[24],"in":[25,104,120],"sense":[27],"it":[29],"bring":[31],"performance":[33,92],"index":[34,83,93,167],"of":[35,70,85,94,136,184,200],"network,":[37],"such":[38],"as":[39,89],"sum":[41,86],"squared":[42,87],"error":[43,49,82,88,166],"(SSE),":[44],"down":[45],"desired":[48],"goal":[50],"much":[51],"faster":[52],"than":[53],"classical":[56],"backpropagation":[57],"(BPA).":[59],"proposed":[61],"based":[65],"on":[66,194],"a":[67,125],"slight":[68],"modification":[69],"Levenberg-Marquardt":[72,98],"(LMA)":[75],"which":[76],"takes":[77],"into":[78],"account":[79],"modified":[81,165],"extension":[84],"new":[91],"network.":[96,186],"uses":[100],"Jacobian":[102,137,153],"matrix":[103,110,138,154],"order":[105],"approximate":[107],"Hessian":[109],"and":[111,117,143,197,203],"most":[115],"important":[116],"difficult":[118],"step":[119],"implementing":[121],"this":[122],"LMA.":[123],"Therefore,":[124],"simple":[126],"technique":[127],"has":[128,171],"been":[129,172],"described":[130],"compute":[132],"first":[133],"transpose":[135],"by":[139,145],"comparing":[140],"two":[141],"equations":[142],"thereafter":[144],"further":[146],"transposing":[147],"former":[149],"one":[150],"actual":[152],"computed":[156],"found":[159],"robust":[162],"against":[163],"extension.":[168],"Furthermore,":[169],"care":[170],"taken":[173],"suppress":[175],"or":[176],"control":[177],"oscillation":[179],"magnitude":[180],"during":[181],"Finally,":[187],"above":[189],"tested":[193],"modeling":[196],"prediction":[198],"applications":[199],"time":[201],"series":[202],"nonlinear":[204],"plant.":[205]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
