{"id":"https://openalex.org/W4200469432","doi":"https://doi.org/10.3233/jifs-210340","title":"Introducing a trapezoidal interval type-2 fuzzy regression model","display_name":"Introducing a trapezoidal interval type-2 fuzzy regression model","publication_year":2021,"publication_date":"2021-12-10","ids":{"openalex":"https://openalex.org/W4200469432","doi":"https://doi.org/10.3233/jifs-210340"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-210340","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-210340","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & 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/A5007116972","display_name":"Mikaeel Mokhtari","orcid":null},"institutions":[{"id":"https://openalex.org/I155419210","display_name":"Islamic Azad University, Science and Research Branch","ror":"https://ror.org/03187yj51","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I155419210"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mikaeel Mokhtari","raw_affiliation_strings":["Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, Iran","institution_ids":["https://openalex.org/I155419210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073095019","display_name":"Tofigh Allahviranloo","orcid":"https://orcid.org/0000-0002-6673-3560"},"institutions":[{"id":"https://openalex.org/I155419210","display_name":"Islamic Azad University, Science and Research Branch","ror":"https://ror.org/03187yj51","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I155419210"]},{"id":"https://openalex.org/I4210121333","display_name":"Istinye University","ror":"https://ror.org/03081nz23","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210121333"]}],"countries":["IR","TR"],"is_corresponding":true,"raw_author_name":"Tofigh Allahviranloo","raw_affiliation_strings":["Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran","Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran","institution_ids":["https://openalex.org/I155419210"]},{"raw_affiliation_string":"Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, Turkey","institution_ids":["https://openalex.org/I4210121333"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008918797","display_name":"Mohammad Hassan Behzadi","orcid":"https://orcid.org/0000-0002-1849-5588"},"institutions":[{"id":"https://openalex.org/I155419210","display_name":"Islamic Azad University, Science and Research Branch","ror":"https://ror.org/03187yj51","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I155419210"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Hassan Behzadi","raw_affiliation_strings":["Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, Iran","institution_ids":["https://openalex.org/I155419210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019808431","display_name":"Farhad Hosseinzadeh Lotf\u0131","orcid":"https://orcid.org/0000-0001-5022-553X"},"institutions":[{"id":"https://openalex.org/I155419210","display_name":"Islamic Azad University, Science and Research Branch","ror":"https://ror.org/03187yj51","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I155419210"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Farhad Hoseinzadeh Lotfi","raw_affiliation_strings":["Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran","institution_ids":["https://openalex.org/I155419210"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073095019"],"corresponding_institution_ids":["https://openalex.org/I155419210","https://openalex.org/I4210121333"],"apc_list":null,"apc_paid":null,"fwci":0.2337,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61931434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"42","issue":"3","first_page":"1381","last_page":"1403"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12135","display_name":"Fuzzy Systems and Optimization","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12135","display_name":"Fuzzy Systems and Optimization","score":1.0,"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"}},{"id":"https://openalex.org/T10050","display_name":"Multi-Criteria Decision Making","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9898999929428101,"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/randomness","display_name":"Randomness","score":0.7604663372039795},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7515149712562561},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6080678105354309},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5603600144386292},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5441712737083435},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46979936957359314},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.455265074968338},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4417809545993805},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.43889251351356506},{"id":"https://openalex.org/keywords/fuzzy-number","display_name":"Fuzzy number","score":0.41234204173088074},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33484727144241333},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3052414655685425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3041613698005676},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22353345155715942}],"concepts":[{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.7604663372039795},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7515149712562561},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6080678105354309},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5603600144386292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5441712737083435},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46979936957359314},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.455265074968338},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4417809545993805},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.43889251351356506},{"id":"https://openalex.org/C1883856","wikidata":"https://www.wikidata.org/wiki/Q3407463","display_name":"Fuzzy number","level":4,"score":0.41234204173088074},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33484727144241333},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3052414655685425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3041613698005676},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22353345155715942},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-210340","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-210340","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W89819432","https://openalex.org/W171604358","https://openalex.org/W1600229293","https://openalex.org/W1972649913","https://openalex.org/W1975267279","https://openalex.org/W1975582241","https://openalex.org/W1988826918","https://openalex.org/W1988880139","https://openalex.org/W1995986371","https://openalex.org/W2006493488","https://openalex.org/W2016525755","https://openalex.org/W2020610055","https://openalex.org/W2023843216","https://openalex.org/W2032845585","https://openalex.org/W2046093040","https://openalex.org/W2049884410","https://openalex.org/W2056386533","https://openalex.org/W2057683820","https://openalex.org/W2059989159","https://openalex.org/W2061318564","https://openalex.org/W2089235815","https://openalex.org/W2096765302","https://openalex.org/W2132911594","https://openalex.org/W2163884893","https://openalex.org/W2171721373","https://openalex.org/W2266726114","https://openalex.org/W2281858122","https://openalex.org/W2306378446","https://openalex.org/W2324733101","https://openalex.org/W2328288079","https://openalex.org/W2394922131","https://openalex.org/W2420737253","https://openalex.org/W2430129705","https://openalex.org/W2527531442","https://openalex.org/W2604527018","https://openalex.org/W2887799891","https://openalex.org/W2897195769","https://openalex.org/W2909033064","https://openalex.org/W2937965166","https://openalex.org/W2968458585","https://openalex.org/W2971811669","https://openalex.org/W2982587061","https://openalex.org/W2983421666","https://openalex.org/W2998003640","https://openalex.org/W3033721517","https://openalex.org/W3044104227","https://openalex.org/W3047323667","https://openalex.org/W4238919913","https://openalex.org/W6679811713","https://openalex.org/W6684236151","https://openalex.org/W6684852082","https://openalex.org/W6695426624","https://openalex.org/W6774518194"],"related_works":["https://openalex.org/W3034924094","https://openalex.org/W3094954546","https://openalex.org/W2981906196","https://openalex.org/W1513698804","https://openalex.org/W4310560702","https://openalex.org/W1486684451","https://openalex.org/W4361273540","https://openalex.org/W2099285375","https://openalex.org/W2801459815","https://openalex.org/W4361984403"],"abstract_inverted_index":{"The":[0],"uncertainty":[1],"is":[2],"an":[3,151],"important":[4],"attribute":[5],"about":[6],"data":[7,32,50,90,277],"that":[8,122],"can":[9,73,248],"arise":[10],"from":[11,92],"different":[12],"sources":[13],"including":[14],"randomness":[15],"and":[16,27,42,70,80,86,125,133,149,169,193,198,205,227,244],"fuzziness,":[17,38,85],"therefore":[18],"in":[19,23,88],"uncertain":[20,93],"environments,":[21],"especially,":[22],"modeling,":[24],"planning,":[25],"decision-making,":[26],"control":[28,82],"under":[29],"uncertainty,":[30],"most":[31],"available":[33],"contain":[34],"some":[35,47,272],"degree":[36],"of":[37,48,83,165,221,231,240,267],"randomness,":[39,84],"or":[40],"both,":[41],"at":[43],"the":[44,58,89,96,139,144,181,191,203,208,219,222,237,241,253,265,268],"same":[45],"time,":[46],"this":[49,56],"may":[51],"be":[52,249],"anomalous":[53],"(outliers).":[54],"In":[55,95,138,180],"regard,":[57],"new":[59,102,111,160,187],"fuzzy":[60,104,115,131,146,167,176,195,259],"regression":[61,106,123,147,254],"approaches":[62],"by":[63,279],"creating":[64],"a":[65,101,110,171,186,213],"functional":[66],"relationship":[67],"between":[68],"response":[69],"explanatory":[71],"variables":[72,127,135],"provide":[74,150,207,285],"efficient":[75],"tools":[76],"to":[77,142,189,201,217,235,251],"explanation,":[78],"prediction":[79],"possibly":[81],"outliers":[87],"obtained":[91],"environments.":[94],"present":[97],"study,":[98],"we":[99,157,184,225,284],"propose":[100,170],"two-stage":[103],"linear":[105],"model":[107,153,210,255,270],"based":[108,211],"on":[109,212],"interval":[112],"type-2":[113],"(IT2)":[114],"least":[116],"absolute":[117],"deviation":[118],"(FLAD)":[119],"method":[120,243],"so":[121],"coefficients":[124,148],"dependent":[126],"are":[128,136],"trapezoidal":[129,258],"IT2":[130,145,166,257],"numbers":[132,168],"independent":[134],"crisp.":[137],"first":[140],"stage,":[141,183],"estimate":[143],"initial":[152],"(by":[154],"original":[155],"dataset),":[156],"introduce":[158,185,226],"two":[159,286],"distance":[161],"measures":[162],"for":[163,174],"comparison":[164],"novel":[172],"framework":[173],"solving":[175],"mathematical":[177],"programming":[178],"problems.":[179],"second":[182],"procedure":[188],"determine":[190],"mild":[192],"extreme":[194],"outlier":[196],"cutoffs":[197],"apply":[199],"them":[200],"remove":[202],"outliers,":[204],"then":[206],"final":[209],"clean":[214],"dataset.":[215],"Furthermore,":[216],"evaluate":[218],"performance":[220,266],"proposed":[223,242,269],"methodology,":[224],"employ":[228],"suitable":[229],"goodness":[230],"fit":[232],"indices.":[233],"Finally,":[234],"illustrate":[236],"theoretical":[238],"results":[239],"explain":[245],"how":[246],"it":[247],"used":[250],"derive":[252],"with":[256,271],"data,":[260],"as":[261,263],"well":[262],"compare":[264],"well-known":[273],"models":[274],"using":[275],"training":[276],"designed":[278],"Tanaka":[280],"et":[281],"al.":[282],"[55],":[283],"numerical":[287],"examples.":[288]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}