{"id":"https://openalex.org/W4400446725","doi":"https://doi.org/10.1109/tfuzz.2024.3421544","title":"Self-Organizing Hybrid Fuzzy Polynomial Neural Network Classifier Driven Through Dynamically Adaptive Structure and Compound Regularization Technique","display_name":"Self-Organizing Hybrid Fuzzy Polynomial Neural Network Classifier Driven Through Dynamically Adaptive Structure and Compound Regularization Technique","publication_year":2024,"publication_date":"2024-07-09","ids":{"openalex":"https://openalex.org/W4400446725","doi":"https://doi.org/10.1109/tfuzz.2024.3421544"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2024.3421544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3421544","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-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/A5100685733","display_name":"Zhen Wang","orcid":"https://orcid.org/0000-0003-3927-0115"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhen Wang","raw_affiliation_strings":["School of Mathematics and Statistics, Linyi University, Linyi, China"],"raw_orcid":"https://orcid.org/0000-0003-3927-0115","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035932097","display_name":"Sung\u2010Kwun Oh","orcid":"https://orcid.org/0000-0001-6798-8955"},"institutions":[{"id":"https://openalex.org/I16764540","display_name":"University of Suwon","ror":"https://ror.org/03ysk5e42","country_code":"KR","type":"education","lineage":["https://openalex.org/I16764540"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung-Kwun Oh","raw_affiliation_strings":["School of Electrical and Electronic Engineering, The University of Suwon, Hwaseong-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-6798-8955","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, The University of Suwon, Hwaseong-si, South Korea","institution_ids":["https://openalex.org/I16764540"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074686535","display_name":"Zunwei Fu","orcid":"https://orcid.org/0000-0001-9109-4142"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zunwei Fu","raw_affiliation_strings":["Research Center for Big Data and Artificial Intelligence, Linyi University, Linyi, China"],"raw_orcid":"https://orcid.org/0000-0001-9109-4142","affiliations":[{"raw_affiliation_string":"Research Center for Big Data and Artificial Intelligence, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003799782","display_name":"Witold Pedrycz","orcid":"https://orcid.org/0000-0002-9335-9930"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Witold Pedrycz","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0002-9335-9930","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034807504","display_name":"Seok-Beom Roh","orcid":"https://orcid.org/0000-0001-7277-6869"},"institutions":[{"id":"https://openalex.org/I55188197","display_name":"Seokyeong University","ror":"https://ror.org/04x0k0m51","country_code":"KR","type":"education","lineage":["https://openalex.org/I55188197"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seok-Beom Roh","raw_affiliation_strings":["Department of Electronic Engineering, Seokyeong University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Seokyeong University, Seoul, South Korea","institution_ids":["https://openalex.org/I55188197"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100347335","display_name":"Jin Hee Yoon","orcid":"https://orcid.org/0000-0002-1437-1350"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin Hee Yoon","raw_affiliation_strings":["Department of Mathematics and Statistics, Sejong University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-1437-1350","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100685733"],"corresponding_institution_ids":["https://openalex.org/I15823474"],"apc_list":null,"apc_paid":null,"fwci":2.3179,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8970689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"32","issue":"9","first_page":"5385","last_page":"5399"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9991999864578247,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.964900016784668,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.62209552526474},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5739755034446716},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5403943061828613},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5146132707595825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5073394179344177},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48182907700538635},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4696559011936188},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4402565658092499},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40861019492149353},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3848021924495697},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34372758865356445}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.62209552526474},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5739755034446716},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5403943061828613},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5146132707595825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5073394179344177},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48182907700538635},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4696559011936188},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4402565658092499},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40861019492149353},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3848021924495697},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34372758865356445},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2024.3421544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3421544","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2733574320","display_name":null,"funder_award_id":"NRF-2023K2A9A2A06060385","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G4170913846","display_name":null,"funder_award_id":"RS-2024-00351610","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G5399602424","display_name":null,"funder_award_id":"12071197","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8634448228","display_name":null,"funder_award_id":"RS-2023-00279445","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1602492977","https://openalex.org/W1998125874","https://openalex.org/W2034824139","https://openalex.org/W2042384216","https://openalex.org/W2071466240","https://openalex.org/W2079880482","https://openalex.org/W2082441352","https://openalex.org/W2125935535","https://openalex.org/W2129463451","https://openalex.org/W2182722412","https://openalex.org/W2519624879","https://openalex.org/W2523594788","https://openalex.org/W2742547131","https://openalex.org/W2776378542","https://openalex.org/W2777602658","https://openalex.org/W2890484132","https://openalex.org/W2993201754","https://openalex.org/W2997546679","https://openalex.org/W3021933602","https://openalex.org/W3080524468","https://openalex.org/W3089892052","https://openalex.org/W3113030340","https://openalex.org/W3135013915","https://openalex.org/W3154745533","https://openalex.org/W3174086521","https://openalex.org/W3191074469","https://openalex.org/W4212901299","https://openalex.org/W4226226325","https://openalex.org/W4229039596","https://openalex.org/W4287889362","https://openalex.org/W4293256647","https://openalex.org/W4312897482","https://openalex.org/W4313291220","https://openalex.org/W4367146573","https://openalex.org/W4385076203","https://openalex.org/W4388505392","https://openalex.org/W4391759741","https://openalex.org/W4392128155","https://openalex.org/W6739879593","https://openalex.org/W6797867632"],"related_works":["https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W1966421350","https://openalex.org/W1868434454","https://openalex.org/W4366985237","https://openalex.org/W2810569973","https://openalex.org/W2128396103","https://openalex.org/W4366984740","https://openalex.org/W4367299891"],"abstract_inverted_index":{"This":[0,131],"study":[1],"presents":[2],"an":[3,51],"innovative":[4],"approach":[5],"to":[6,82,98,135,137,174],"the":[7,19,56,67,79,100,119,127,133,138,146,152,156,176,182,191,194,210,240,246,252,260],"design":[8],"of":[9,22,69,112,115,140,151,159,178,184,190,209,245,259],"a":[10,15,23,85,95,107,200,256,269],"hybrid":[11,34],"fuzzy":[12,25,35,87,120,220],"classifier,":[13],"with":[14],"focus":[16],"on":[17,65],"exploring":[18,66],"classification":[20,141,274],"capability":[21],"conventional":[24],"polynomial":[26,36,88,122,128],"neural":[27,89],"network":[28,53,90,179],"(CFPNN).":[29],"The":[30,103,207,248],"proposed":[31,101,104,211],"novel":[32],"self-organizing":[33],"NN":[37],"classifier":[38,134],"(HFPNNC)":[39],"improves":[40],"performance":[41],"while":[42],"maintaining":[43],"model":[44,203],"interpretability":[45],"and":[46,55,125,148,166,181,196,205,222,234,251],"fixability":[47],"by":[48],"synergistically":[49],"combining":[50],"adaptive":[52,109],"structure":[54,91,110],"compound":[57],"regularization":[58,168],"technique":[59],"(CRT).":[60],"Recent":[61],"studies":[62],"have":[63],"focused":[64],"potential":[68,267],"CFPNN":[70,80],"structures":[71],"for":[72,273],"addressing":[73],"regression":[74],"issues.":[75],"To":[76,143],"effectively":[77],"introduce":[78],"framework":[81],"multiclassification":[83],"tasks,":[84],"resilient":[86],"was":[92],"designed":[93],"as":[94,268],"basic":[96],"subclassifier":[97],"construct":[99],"HFPNNC.":[102],"HFPNNC":[105,212,238,261],"employs":[106],"dynamically":[108],"comprising":[111],"two":[113,231],"types":[114],"critical":[116],"layers:":[117],"1)":[118],"set-based":[121],"neurons":[123,129],"layers":[124,180],"2)":[126],"layers.":[130],"allows":[132],"adapt":[136],"complexity":[139,204],"tasks.":[142,275],"further":[144],"strengthen":[145],"robustness":[147],"generalization":[149],"ability":[150],"HFPNNC,":[153],"we":[154],"incorporate":[155],"synergistic":[157],"combination":[158],"probabilistic":[160],"constrained":[161],"competitive":[162],"response":[163],"selection":[164],"(PCCRS)":[165],"\u21132-norm":[167],"least":[169],"squares":[170],"estimation":[171,183],"(\u21132-LSE)":[172],"methods":[173],"manage":[175],"generation":[177],"neuron":[185],"weights.":[186],"As":[187],"key":[188],"constituents":[189],"CRT":[192],"approach,":[193],"PCCRS":[195],"\u21132-LSE":[197],"method":[198],"strike":[199],"balance":[201],"between":[202],"performance.":[206],"effectiveness":[208],"is":[213],"thoroughly":[214],"evaluated":[215],"against":[216],"classical":[217],"classifiers,":[218],"state-of-the-art":[219],"classifiers":[221],"deep":[223],"learning":[224],"baseline":[225],"models":[226],"using":[227],"17":[228],"public":[229],"datasets,":[230,233],"real-world":[232],"three":[235],"large-scale":[236],"datasets.":[237],"achieves":[239],"best":[241],"prediction":[242],"in":[243],"72.7%":[244],"data.":[247],"experimental":[249],"results":[250],"statistical":[253],"analysis":[254],"show":[255],"remarkable":[257],"advantage":[258],"over":[262],"existing":[263],"methods,":[264],"confirming":[265],"its":[266],"flexible,":[270],"interpretable":[271],"solution":[272]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
