{"id":"https://openalex.org/W7142006539","doi":"https://doi.org/10.1155/cplx/3937849","title":"Design of a TSK Rule\u2010Based Model With Granular Rules and Ensemble Learning in Big Data","display_name":"Design of a TSK Rule\u2010Based Model With Granular Rules and Ensemble Learning in Big Data","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7142006539","doi":"https://doi.org/10.1155/cplx/3937849"},"language":"en","primary_location":{"id":"doi:10.1155/cplx/3937849","is_oa":true,"landing_page_url":"https://doi.org/10.1155/cplx/3937849","pdf_url":null,"source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1155/cplx/3937849","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mohammad Nematpour","orcid":"https://orcid.org/0000-0001-7947-5364"},"institutions":[{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Nematpour","raw_affiliation_strings":["Department of Computer Science ,  Faculty of Mathematical Sciences ,  University of Tabriz ,  Tabriz ,  Iran ,  tabrizu.ac.ir"],"raw_orcid":"https://orcid.org/0000-0001-7947-5364","affiliations":[{"raw_affiliation_string":"Department of Computer Science ,  Faculty of Mathematical Sciences ,  University of Tabriz ,  Tabriz ,  Iran ,  tabrizu.ac.ir","institution_ids":["https://openalex.org/I41832843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071285018","display_name":"Farnaz Mahan","orcid":"https://orcid.org/0000-0002-9215-6015"},"institutions":[{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Farnaz Mahan","raw_affiliation_strings":["Department of Computer Science ,  Faculty of Mathematical Sciences ,  University of Tabriz ,  Tabriz ,  Iran ,  tabrizu.ac.ir"],"raw_orcid":"https://orcid.org/0000-0002-9215-6015","affiliations":[{"raw_affiliation_string":"Department of Computer Science ,  Faculty of Mathematical Sciences ,  University of Tabriz ,  Tabriz ,  Iran ,  tabrizu.ac.ir","institution_ids":["https://openalex.org/I41832843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130846155","display_name":"Witold Pedrycz","orcid":null},"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 ,  Faculty of Engineering ,  University of Alberta ,  Edmonton ,  T6G 2H5 , Alberta,  Canada ,  ualberta.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering ,  Faculty of Engineering ,  University of Alberta ,  Edmonton ,  T6G 2H5 , Alberta,  Canada ,  ualberta.ca","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081904136","display_name":"Habib Izadkhah","orcid":"https://orcid.org/0000-0001-7595-8350"},"institutions":[{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Habib Izadkhah","raw_affiliation_strings":["Department of Computer Science ,  Faculty of Mathematical Sciences ,  University of Tabriz ,  Tabriz ,  Iran ,  tabrizu.ac.ir"],"raw_orcid":"https://orcid.org/0000-0001-7595-8350","affiliations":[{"raw_affiliation_string":"Department of Computer Science ,  Faculty of Mathematical Sciences ,  University of Tabriz ,  Tabriz ,  Iran ,  tabrizu.ac.ir","institution_ids":["https://openalex.org/I41832843"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071285018"],"corresponding_institution_ids":["https://openalex.org/I41832843"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.65688381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2026","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.39239999651908875,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.39239999651908875,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.13910000026226044,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.05849999934434891,"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/big-data","display_name":"Big data","score":0.829200029373169},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5932999849319458},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5569999814033508},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5246000289916992},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5144000053405762},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45910000801086426},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.4302000105381012},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4124999940395355}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.829200029373169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8115000128746033},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6363999843597412},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5932999849319458},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5569999814033508},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5246000289916992},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5144000053405762},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45910000801086426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45750001072883606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4417000114917755},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.4302000105381012},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4081999957561493},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C201932085","wikidata":"https://www.wikidata.org/wiki/Q642514","display_name":"Online analytical processing","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.2696000039577484},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/cplx/3937849","is_oa":true,"landing_page_url":"https://doi.org/10.1155/cplx/3937849","pdf_url":null,"source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2307404a1784440b8c7f4d60d805ba30","is_oa":true,"landing_page_url":"https://doaj.org/article/2307404a1784440b8c7f4d60d805ba30","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2026 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/cplx/3937849","is_oa":true,"landing_page_url":"https://doi.org/10.1155/cplx/3937849","pdf_url":null,"source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5514742732048035}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2475933805","https://openalex.org/W2763579727","https://openalex.org/W2772558023","https://openalex.org/W2782832634","https://openalex.org/W2908492648","https://openalex.org/W2944920266","https://openalex.org/W2952191418","https://openalex.org/W3097821058","https://openalex.org/W3136933010","https://openalex.org/W4220750254","https://openalex.org/W4221049491","https://openalex.org/W4242247902","https://openalex.org/W4297433427","https://openalex.org/W4320525798","https://openalex.org/W4320725980","https://openalex.org/W4360603925","https://openalex.org/W4367309379","https://openalex.org/W4376471445","https://openalex.org/W4379875180","https://openalex.org/W4386142022","https://openalex.org/W4387196076","https://openalex.org/W4389261517","https://openalex.org/W4392641400","https://openalex.org/W4393153206","https://openalex.org/W4393262906","https://openalex.org/W4394575236","https://openalex.org/W4399838007","https://openalex.org/W4399896452","https://openalex.org/W4401111399","https://openalex.org/W4401894821","https://openalex.org/W4402758860","https://openalex.org/W4404061168","https://openalex.org/W4404371042"],"related_works":[],"abstract_inverted_index":{"Nowadays,":[0],"the":[1,15,28,35,66,70,99,155,163,178,181,188],"management":[2],"and":[3,90,97,122,171],"analysis":[4,42],"of":[5,17,23,37,69,101,113,180],"big":[6,40,77,105],"data":[7,18,24,41,78,106,121],"have":[8,50],"become":[9],"major":[10],"challenges":[11],"for":[12,55,76,95],"researchers":[13],"in":[14,104,154],"field":[16],"mining.":[19],"The":[20,126,184],"increasing":[21],"rate":[22],"generation,":[25],"along":[26],"with":[27,141,168],"need":[29],"to":[30,81,158,175],"extract":[31],"meaningful":[32],"patterns,":[33],"highlights":[34],"necessity":[36],"developing":[38],"scalable":[39],"methods.":[43],"In":[44,162],"this":[45,109],"context,":[46],"fuzzy":[47],"rule\u2010based":[48,102,114],"models":[49,63,103],"emerged":[51],"as":[52],"powerful":[53],"tools":[54],"knowledge":[56],"extraction":[57],"from":[58,129],"data.":[59],"However,":[60],"designing":[61,96],"these":[62,130],"typically":[64],"requires":[65],"monolithic":[67],"use":[68],"entire":[71],"dataset,":[72],"which":[73,148],"is":[74],"impractical":[75],"scenarios":[79],"due":[80],"computational":[82],"limitations.":[83],"This":[84,146],"study":[85],"introduces":[86],"a":[87,92,111],"novel":[88],"concept":[89],"proposes":[91],"new":[93],"framework":[94],"evaluating":[98],"performance":[100,179],"environments.":[107],"Within":[108],"framework,":[110],"set":[112],"submodels":[115,131],"are":[116,132,173],"randomly":[117],"constructed":[118],"using":[119,135],"sampled":[120],"trained":[123],"through":[124],"Bagging.":[125],"rules":[127],"extracted":[128],"then":[133],"aggregated":[134],"an":[136,142],"optimization\u2010based":[137],"weighting":[138],"strategy":[139],"combined":[140],"information":[143],"entropy":[144],"method.":[145],"approach,":[147],"has":[149],"not":[150],"yet":[151],"been":[152],"explored":[153],"literature,":[156],"contributes":[157],"improving":[159],"model":[160,190],"efficiency.":[161],"experimental":[164],"section,":[165],"large\u2010scale":[166],"datasets":[167],"high":[169],"dimensionality":[170],"volume":[172],"employed":[174],"comprehensively":[176],"evaluate":[177],"proposed":[182,189],"model.":[183],"results":[185],"demonstrate":[186],"that":[187],"achieves":[191],"significant":[192],"improvements":[193],"over":[194],"comparable":[195],"models.":[196]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-03-29T00:00:00"}