{"id":"https://openalex.org/W2978624412","doi":"https://doi.org/10.1109/ijcnn.2019.8852310","title":"Unbounded Recurrent Fuzzy Min-Max Neural Network for Pattern Classification","display_name":"Unbounded Recurrent Fuzzy Min-Max Neural Network for Pattern Classification","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978624412","doi":"https://doi.org/10.1109/ijcnn.2019.8852310","mag":"2978624412"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5081062079","display_name":"Jaishri M. Waghmare","orcid":"https://orcid.org/0000-0002-3403-6410"},"institutions":[{"id":"https://openalex.org/I4210093989","display_name":"Sanskriti Samvardhan Mandal","ror":"https://ror.org/01egfqj98","country_code":"IN","type":"other","lineage":["https://openalex.org/I4210093989"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jaishri M. Waghmare","raw_affiliation_strings":["Department of Computer Science & Engineering, SGGSIE&T, Nanded, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, SGGSIE&T, Nanded, India","institution_ids":["https://openalex.org/I4210093989"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103355149","display_name":"U. V. Kulkarni","orcid":null},"institutions":[{"id":"https://openalex.org/I4210093989","display_name":"Sanskriti Samvardhan Mandal","ror":"https://ror.org/01egfqj98","country_code":"IN","type":"other","lineage":["https://openalex.org/I4210093989"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Uday V. Kulkarni","raw_affiliation_strings":["Department of Computer Science & Engineering, SGGSIE&T, Nanded, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, SGGSIE&T, Nanded, India","institution_ids":["https://openalex.org/I4210093989"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081062079"],"corresponding_institution_ids":["https://openalex.org/I4210093989"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66139514,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","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/T10820","display_name":"Fuzzy Logic and Control Systems","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/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6279342770576477},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5735633969306946},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.484222412109375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47233620285987854},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4660286605358124},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4604170620441437},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4447939097881317},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44126901030540466},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.42822057008743286},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3483123779296875},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3330972194671631},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29217228293418884}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6279342770576477},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5735633969306946},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.484222412109375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47233620285987854},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4660286605358124},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4604170620441437},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4447939097881317},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44126901030540466},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.42822057008743286},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3483123779296875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3330972194671631},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29217228293418884},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W78030844","https://openalex.org/W1480067276","https://openalex.org/W1556849636","https://openalex.org/W1636682230","https://openalex.org/W1823785159","https://openalex.org/W1965755769","https://openalex.org/W1983339194","https://openalex.org/W2007187232","https://openalex.org/W2013955970","https://openalex.org/W2016883203","https://openalex.org/W2023459309","https://openalex.org/W2082381659","https://openalex.org/W2082684957","https://openalex.org/W2106980479","https://openalex.org/W2113772493","https://openalex.org/W2114770214","https://openalex.org/W2127436605","https://openalex.org/W2129021863","https://openalex.org/W2145747704","https://openalex.org/W2168603260","https://openalex.org/W2513776656","https://openalex.org/W3120740533","https://openalex.org/W6633338241","https://openalex.org/W6726095823"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4230315250"],"abstract_inverted_index":{"A":[0],"prominent":[1],"stumbling":[2],"block":[3],"in":[4,40,109,158],"use":[5],"of":[6,62,77,92,131,141,174],"the":[7,22,41,71,78,90,98,122,132,148,167,172,180,196],"original":[8],"fuzzy":[9],"min-max":[10],"neural":[11],"network":[12],"(FMN)":[13],"and":[14,44,143,162],"other":[15],"FMN-based":[16],"algorithms":[17,31,66,105],"is":[18,46,186,193],"their":[19],"sensitivity":[20],"to":[21,33,49,86,97,147],"expansion":[23,27,79,133],"coefficient":[24,134],"or":[25,95,177],"hyperbox":[26],"parameter.":[28],"Specifically,":[29],"these":[30,65,104],"need":[32,181],"be":[34,87],"trained":[35],"with":[36,58,151],"its":[37,83],"different":[38,75,139],"values":[39,76],"range":[42],"[0,1],":[43],"it":[45,170,185],"adjusted":[47],"appropriately":[48],"obtain":[50],"100":[51],"percent":[52],"accuracy":[53],"for":[54,74,89,138,182],"training":[55,72],"data":[56,73,198],"set":[57],"a":[59,110,152],"minimum":[60],"number":[61],"hyperboxes.":[63],"Hence,":[64],"execute":[67],"multiple":[68],"passes":[69],"over":[70],"coefficient.":[80],"Moreover,":[81,165],"usually,":[82],"value":[84],"has":[85],"retuned":[88],"addition":[91,173],"new":[93,175],"patterns":[94,176],"classes":[96,178],"existing":[99],"classifier.":[100],"Consequently,":[101],"as":[102,129],"expected":[103],"do":[106],"not":[107],"learn":[108],"single":[111],"pass.":[112],"This":[113],"paper":[114],"proposes":[115],"an":[116,187],"Unbounded":[117],"Recurrent":[118],"FMN":[119],"(URFMN).":[120],"In":[121],"URFMN,":[123],"several":[124],"modifications":[125],"are":[126],"proposed":[127],"such":[128],"removal":[130],"parameter,":[135],"membership":[136],"functions":[137],"types":[140],"hyperboxes,":[142],"metamorphosis":[144],"from":[145],"feed-forward":[146],"recurrent":[149],"topology":[150],"novel":[153],"learning":[154],"algorithm":[155],"which":[156],"works":[157],"two":[159],"phases-":[160],"offline":[161],"online":[163,168,188],"phase.":[164],"during":[166],"phase,":[169],"allows":[171],"without":[179],"retraining.":[183],"Hence":[184],"adaptive":[189],"algorithm.":[190],"Its":[191],"performance":[192],"evaluated":[194],"using":[195],"benchmark":[197],"sets.":[199]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
