{"id":"https://openalex.org/W7204943022","doi":"https://doi.org/10.31466/kfbd.1808266","title":"Regression Analysis with Type-1 Fuzzy Functions and Feature Selection Methods","display_name":"Regression Analysis with Type-1 Fuzzy Functions and Feature Selection Methods","publication_year":2026,"publication_date":"2026-09-01","ids":{"openalex":"https://openalex.org/W7204943022","doi":"https://doi.org/10.31466/kfbd.1808266"},"language":"tr","primary_location":{"id":"doi:10.31466/kfbd.1808266","doi":"https://doi.org/10.31466/kfbd.1808266","is_oa":true,"landing_page_url":"https://doi.org/10.31466/kfbd.1808266","pdf_url":null,"source":{"id":"https://openalex.org/S4210214690","display_name":"Karadeniz Fen Bilimleri Dergisi","issn_l":"1309-4726","issn":["1309-4726","2564-7377"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","tr-dizin"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Karadeniz Fen Bilimleri Dergisi","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.31466/kfbd.1808266","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148844561","display_name":"Mehmet Emin \u015eahin","orcid":"https://orcid.org/0009-0005-3458-976X","observed_orcids":["https://orcid.org/0009-0005-3458-976X"]},"institutions":[{"id":"https://openalex.org/I74897591","display_name":"Marmara University","ror":"https://ror.org/02kswqa67","country_code":"TR","type":"education","lineage":["https://openalex.org/I74897591"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Mehmet Emin \u015eahin","raw_affiliation_strings":["MARMARA \u00dcN\u0130VERS\u0130TES\u0130"],"raw_orcid":"https://orcid.org/0009-0005-3458-976X","affiliations":[{"raw_affiliation_string":"MARMARA \u00dcN\u0130VERS\u0130TES\u0130","institution_ids":["https://openalex.org/I74897591"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020166333","display_name":"Nihat Tak","orcid":"https://orcid.org/0000-0001-8796-5101","observed_orcids":["https://orcid.org/0000-0001-8796-5101"]},"institutions":[{"id":"https://openalex.org/I74897591","display_name":"Marmara University","ror":"https://ror.org/02kswqa67","country_code":"TR","type":"education","lineage":["https://openalex.org/I74897591"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Nihat Tak","raw_affiliation_strings":["MARMARA \u00dcN\u0130VERS\u0130TES\u0130"],"raw_orcid":"https://orcid.org/0000-0001-8796-5101","affiliations":[{"raw_affiliation_string":"MARMARA \u00dcN\u0130VERS\u0130TES\u0130","institution_ids":["https://openalex.org/I74897591"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74897591"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64661566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"3","first_page":"1135","last_page":"1155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.7821999788284302,"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":0.7821999788284302,"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":0.18289999663829803,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.004399999976158142,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fuzzy-regression","display_name":"fuzzy regression","score":0.871999979019165},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.8820000290870667},{"id":"https://openalex.org/keywords/lasso","display_name":"LASSO","score":0.9660000205039978},{"id":"https://openalex.org/keywords/multicollinearity","display_name":"multicollinearity","score":0.9739999771118164},{"id":"https://openalex.org/keywords/nonlinear-regression","display_name":"nonlinear regression","score":0.8069999814033508},{"id":"https://openalex.org/keywords/regularization","display_name":"regularization","score":0.7900000214576721},{"id":"https://openalex.org/keywords/forward-selection","display_name":"forward selection","score":0.5600000023841858},{"id":"https://openalex.org/keywords/uncertainty-modeling","display_name":"uncertainty modeling","score":0.3440000116825104}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7075999975204468},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5340999960899353},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.5041999816894531},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47929999232292175},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4458000063896179},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44429999589920044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4237000048160553},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C46889948","wikidata":"https://www.wikidata.org/wiki/Q2755024","display_name":"Nonlinear regression","level":3,"score":0.35659998655319214},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.3086000084877014},{"id":"https://openalex.org/C44882253","wikidata":"https://www.wikidata.org/wiki/Q3455882","display_name":"Multivariate adaptive regression splines","level":4,"score":0.30379998683929443},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.3034999966621399},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.2897000014781952},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.31466/kfbd.1808266","doi":"https://doi.org/10.31466/kfbd.1808266","is_oa":true,"landing_page_url":"https://doi.org/10.31466/kfbd.1808266","pdf_url":null,"source":{"id":"https://openalex.org/S4210214690","display_name":"Karadeniz Fen Bilimleri Dergisi","issn_l":"1309-4726","issn":["1309-4726","2564-7377"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","tr-dizin"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Karadeniz Fen Bilimleri Dergisi","raw_type":"journal-article"},{"id":"pmh:oai:dergipark.org.tr:article/1808266","doi":null,"is_oa":true,"landing_page_url":"https://dergipark.org.tr/en/pub/kfbd/article/1808266","pdf_url":null,"source":{"id":"https://openalex.org/S4306401840","display_name":"DergiPark (Istanbul University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67581229","host_organization_name":"Istanbul University","host_organization_lineage":["https://openalex.org/I67581229"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Karadeniz Fen Bilimleri Dergisi, Vol. 16 No. 3","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.31466/kfbd.1808266","doi":"https://doi.org/10.31466/kfbd.1808266","is_oa":true,"landing_page_url":"https://doi.org/10.31466/kfbd.1808266","pdf_url":null,"source":{"id":"https://openalex.org/S4210214690","display_name":"Karadeniz Fen Bilimleri Dergisi","issn_l":"1309-4726","issn":["1309-4726","2564-7377"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","tr-dizin"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Karadeniz Fen Bilimleri Dergisi","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2504188341","display_name":null,"funder_award_id":"123F266","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"}],"funders":[{"id":"https://openalex.org/F4320322626","display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","ror":"https://ror.org/04w9kkr77"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1513618424","https://openalex.org/W1523985187","https://openalex.org/W1605276600","https://openalex.org/W1986528915","https://openalex.org/W1993387039","https://openalex.org/W1995461802","https://openalex.org/W2012110609","https://openalex.org/W2017337590","https://openalex.org/W2079325629","https://openalex.org/W2114060717","https://openalex.org/W2135046866","https://openalex.org/W2142635246","https://openalex.org/W2143426320","https://openalex.org/W2487770199","https://openalex.org/W2502759836","https://openalex.org/W2568426016","https://openalex.org/W2625141987","https://openalex.org/W2972206197","https://openalex.org/W4211007335","https://openalex.org/W4234698323","https://openalex.org/W4249749961","https://openalex.org/W4293254998","https://openalex.org/W4311569069","https://openalex.org/W4399921433","https://openalex.org/W4403609992"],"related_works":["https://openalex.org/W7119495740","https://openalex.org/W4389265753","https://openalex.org/W1869713303","https://openalex.org/W3088441116","https://openalex.org/W4293192452","https://openalex.org/W7161995191","https://openalex.org/W2600746833","https://openalex.org/W4416345380","https://openalex.org/W7117868251","https://openalex.org/W4296441075"],"abstract_inverted_index":{"Real-world":[0],"regression":[1,39,193],"problems":[2],"often":[3],"involve":[4],"noise,":[5],"redundancy,":[6],"multicollinearity,":[7],"and":[8,71,97,103,119,145,153,159,179,189],"nonlinear":[9,72],"relationships":[10],"that":[11,111,175],"limit":[12],"the":[13,35,41,60,126,137,151,164,172,183],"effectiveness":[14],"of":[15,37],"classical":[16,116],"models.":[17],"This":[18],"study":[19],"investigates":[20],"Type-1":[21],"Fuzzy":[22,55],"Functions":[23],"(T1FF)":[24],"combined":[25],"with":[26,31],"several":[27],"feature":[28,177],"selection":[29,178],"strategies,":[30],"particular":[32],"emphasis":[33],"on":[34,76,85,122,132,150,195],"integration":[36],"Lasso":[38,120],"into":[40,59,182],"T1FF":[42,63,128,139,161,184],"framework,":[43],"which":[44],"has":[45],"not":[46],"been":[47],"directly":[48],"examined":[49],"in":[50],"prior":[51],"research.":[52],"By":[53],"incorporating":[54],"C-Means-based":[56],"membership":[57],"degrees":[58],"modelling":[61,194],"process,":[62],"provides":[64,186],"a":[65,187],"flexible":[66,190],"way":[67],"to":[68],"capture":[69],"uncertainty":[70],"structure":[73],"without":[74],"relying":[75],"expert-defined":[77],"fuzzy":[78],"rules.":[79],"The":[80,108],"proposed":[81],"framework":[82,185],"was":[83],"evaluated":[84],"six":[86],"datasets,":[87,124,156],"namely":[88],"Boston,":[89],"Auto,":[90],"College,":[91],"Steel":[92],"Fatigue":[93],"Strength,":[94],"Fish":[95,154],"Price,":[96],"Smart":[98],"Pressure":[99],"Control,":[100],"using":[101],"RMSE":[102],"MAPE":[104],"as":[105],"performance":[106,149],"criteria.":[107],"results":[109,143],"show":[110],"T1FF-based":[112],"models":[113,121],"generally":[114],"outperform":[115],"LM,":[117],"Ridge,":[118],"most":[123,165],"although":[125],"best-performing":[127],"variant":[129],"varied":[130],"depending":[131],"dataset":[133],"characteristics.":[134],"In":[135],"particular,":[136],"Lasso-based":[138],"model":[140],"yielded":[141],"competitive":[142],"overall":[144],"achieved":[146],"especially":[147],"strong":[148],"College":[152],"Price":[155],"while":[157],"Full":[158],"Forward":[160],"methods":[162,181],"showed":[163],"consistent":[166],"MAPE-based":[167],"ranking":[168],"across":[169],"datasets.":[170],"Overall,":[171],"findings":[173],"indicate":[174],"integrating":[176],"regularization":[180],"promising":[188],"approach":[191],"for":[192],"complex":[196],"real-world":[197],"data.":[198]},"counts_by_year":[],"updated_date":"2026-09-11T09:22:31.653822","created_date":"2026-09-02T00:00:00"}