{"id":"https://openalex.org/W2750239752","doi":"https://doi.org/10.1109/fuzz-ieee.2017.8015718","title":"Developing deep fuzzy network with Takagi Sugeno fuzzy inference system","display_name":"Developing deep fuzzy network with Takagi Sugeno fuzzy inference system","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2750239752","doi":"https://doi.org/10.1109/fuzz-ieee.2017.8015718","mag":"2750239752"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2017.8015718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2017.8015718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5014311749","display_name":"Shreedharkumar D. Rajurkar","orcid":null},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Shreedharkumar Rajurkar","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014147535","display_name":"Nishchal K. Verma","orcid":"https://orcid.org/0000-0001-8752-5616"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nishchal Kumar Verma","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014311749"],"corresponding_institution_ids":["https://openalex.org/I94234084"],"apc_list":null,"apc_paid":null,"fwci":4.0954,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.9518396,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9998999834060669,"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":0.9998999834060669,"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":0.996999979019165,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9708999991416931,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.7196955680847168},{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.6963748931884766},{"id":"https://openalex.org/keywords/neuro-fuzzy","display_name":"Neuro-fuzzy","score":0.6648519039154053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6363670229911804},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5412977933883667},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.5367395281791687},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5136141777038574},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.46244722604751587},{"id":"https://openalex.org/keywords/vagueness","display_name":"Vagueness","score":0.4487093389034271},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4445697069168091},{"id":"https://openalex.org/keywords/fuzzy-set-operations","display_name":"Fuzzy set operations","score":0.44314101338386536},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4403298795223236},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42990797758102417},{"id":"https://openalex.org/keywords/fuzzy-rule","display_name":"Fuzzy rule","score":0.41544464230537415},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35775071382522583}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7196955680847168},{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.6963748931884766},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.6648519039154053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6363670229911804},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5412977933883667},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.5367395281791687},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5136141777038574},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46244722604751587},{"id":"https://openalex.org/C2776825360","wikidata":"https://www.wikidata.org/wiki/Q1411921","display_name":"Vagueness","level":3,"score":0.4487093389034271},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4445697069168091},{"id":"https://openalex.org/C148671577","wikidata":"https://www.wikidata.org/wiki/Q5511133","display_name":"Fuzzy set operations","level":4,"score":0.44314101338386536},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4403298795223236},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42990797758102417},{"id":"https://openalex.org/C2780049643","wikidata":"https://www.wikidata.org/wiki/Q5511139","display_name":"Fuzzy rule","level":4,"score":0.41544464230537415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35775071382522583}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2017.8015718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2017.8015718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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":23,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W1507773449","https://openalex.org/W1554663460","https://openalex.org/W1964468250","https://openalex.org/W1987385632","https://openalex.org/W1988304669","https://openalex.org/W1993882792","https://openalex.org/W2002041997","https://openalex.org/W2009163533","https://openalex.org/W2015701733","https://openalex.org/W2027197837","https://openalex.org/W2050288270","https://openalex.org/W2079325629","https://openalex.org/W2088447802","https://openalex.org/W2103269436","https://openalex.org/W2137983211","https://openalex.org/W2163605009","https://openalex.org/W2178155017","https://openalex.org/W2247742123","https://openalex.org/W2417420127","https://openalex.org/W2525305541","https://openalex.org/W3146803896","https://openalex.org/W4388297464"],"related_works":["https://openalex.org/W1822851171","https://openalex.org/W2135891541","https://openalex.org/W2148203161","https://openalex.org/W2165718806","https://openalex.org/W32657058","https://openalex.org/W2730301319","https://openalex.org/W3084323704","https://openalex.org/W2109441327","https://openalex.org/W591834135","https://openalex.org/W1967710160"],"abstract_inverted_index":{"The":[0,156,179,195,221],"state-of-art":[1,21],"algorithms":[2,22],"in":[3,12,45,52,151,153,176,202,236],"computational":[4],"intelligence":[5,11],"have":[6,23,73],"become":[7],"better":[8],"than":[9],"human":[10,69],"some":[13],"of":[14,19,29,36,79,90,107,161,165,197,214],"pattern":[15],"recognition":[16],"areas.":[17],"Most":[18],"these":[20],"been":[24,43,74],"developed":[25,110],"from":[26,111],"the":[27,97,177,225],"concept":[28],"multi-layered":[30,108],"artificial":[31,86,215,233],"neural":[32,87,216,234],"networks.":[33,88],"Large":[34],"amount":[35],"numerical":[37],"and":[38,59,85,205,208],"linguistic":[39,65],"rule":[40],"data":[41],"has":[42],"created":[44],"recent":[46],"years.":[47],"Fuzzy":[48,61,128],"sets":[49],"are":[50,188],"useful":[51],"modeling":[53],"uncertainty":[54],"due":[55],"to":[56,68,76],"vagueness,":[57],"ambiguity":[58],"imprecision.":[60],"inference":[62,83,94,115,133],"systems":[63,84,116],"incorporate":[64],"rules":[66],"intelligible":[67],"beings.":[70],"Many":[71],"attempts":[72],"made":[75],"combine":[77],"assets":[78],"fuzzy":[80,82,93,114,132,147,169],"sets,":[81],"Use":[89],"a":[91,104],"single":[92],"system":[95],"limits":[96],"performance.":[98],"In":[99],"this":[100,154],"paper,":[101],"we":[102],"propose":[103],"generic":[105,121,157],"architecture":[106,122,181,199,227],"network":[109,148,163,170,217,235],"Takagi":[112],"Sugeno":[113,126],"as":[117,182,184],"basic":[118],"units.":[119],"This":[120],"is":[123,149,174,200,210],"called":[124],"\u201cTakagi":[125],"Deep":[127],"Network\u201d.":[129],"Multiple":[130],"distinct":[131],"structures":[134],"can":[135],"be":[136],"identified":[137],"using":[138,171,190],"proposed":[139,180,198,226],"architecture.":[140,220],"A":[141],"general":[142],"three":[143,166,230],"layered":[144,167,231],"TS":[145],"deep":[146,168],"explained":[150],"detail":[152],"paper.":[155,178],"algorithm":[158],"for":[159],"identification":[160,186],"all":[162,237],"parameters":[164],"error":[172],"backpropagation":[173],"presented":[175],"well":[183],"its":[185],"procedure":[187],"validated":[189],"two":[191],"experimental":[192],"case":[193],"studies.":[194],"performance":[196,213],"evaluated":[201],"normal,":[203],"imprecise":[204],"vague":[206],"situations":[207],"it":[209],"compared":[211],"with":[212,218],"same":[219],"results":[222],"illustrate":[223],"that":[224],"eclipses":[228],"over":[229],"feedforward":[232],"situations.":[238]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
