{"id":"https://openalex.org/W2910487174","doi":"https://doi.org/10.1109/tfuzz.2019.2893863","title":"Intuitionistic Fuzzy Twin Support Vector Machines","display_name":"Intuitionistic Fuzzy Twin Support Vector Machines","publication_year":2019,"publication_date":"2019-01-17","ids":{"openalex":"https://openalex.org/W2910487174","doi":"https://doi.org/10.1109/tfuzz.2019.2893863","mag":"2910487174"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2019.2893863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2019.2893863","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on 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/A5027876615","display_name":"Salim Rezvani","orcid":"https://orcid.org/0000-0002-2277-5654"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Salim Rezvani","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, College of Computer Science and Software Engineering, Big Data Institute, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2277-5654","affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, College of Computer Science and Software Engineering, Big Data Institute, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073006299","display_name":"Xizhao Wang","orcid":"https://orcid.org/0000-0001-6036-4728"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xizhao Wang","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, College of Computer Science and Software Engineering, Big Data Institute, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6036-4728","affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, College of Computer Science and Software Engineering, Big Data Institute, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031691031","display_name":"Farhad Pourpanah","orcid":"https://orcid.org/0000-0002-7122-9975"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Farhad Pourpanah","raw_affiliation_strings":["College of Mathematics and Statistics, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027876615"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":6.6337,"has_fulltext":false,"cited_by_count":166,"citation_normalized_percentile":{"value":0.97381234,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"27","issue":"11","first_page":"2140","last_page":"2151"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9941999912261963,"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":0.9934999942779541,"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/support-vector-machine","display_name":"Support vector machine","score":0.789604663848877},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6126152276992798},{"id":"https://openalex.org/keywords/hyperplane","display_name":"Hyperplane","score":0.5708619952201843},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.534271776676178},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5306075215339661},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46509137749671936},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.46041351556777954},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4571324586868286},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43507885932922363},{"id":"https://openalex.org/keywords/structural-risk-minimization","display_name":"Structural risk minimization","score":0.4301382303237915},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4216769337654114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3915177285671234},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3596940040588379},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3342772126197815}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.789604663848877},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6126152276992798},{"id":"https://openalex.org/C68693459","wikidata":"https://www.wikidata.org/wiki/Q657586","display_name":"Hyperplane","level":2,"score":0.5708619952201843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.534271776676178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5306075215339661},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46509137749671936},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.46041351556777954},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4571324586868286},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43507885932922363},{"id":"https://openalex.org/C154507838","wikidata":"https://www.wikidata.org/wiki/Q7625053","display_name":"Structural risk minimization","level":3,"score":0.4301382303237915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4216769337654114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3915177285671234},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3596940040588379},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3342772126197815},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2019.2893863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2019.2893863","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4835894923","display_name":null,"funder_award_id":"61772344","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6813436119","display_name":null,"funder_award_id":"61732011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W649301306","https://openalex.org/W1221277128","https://openalex.org/W1678356000","https://openalex.org/W1752482607","https://openalex.org/W1994807229","https://openalex.org/W1995013121","https://openalex.org/W1995945562","https://openalex.org/W1999466278","https://openalex.org/W2001305057","https://openalex.org/W2014908235","https://openalex.org/W2019184604","https://openalex.org/W2039073241","https://openalex.org/W2046384674","https://openalex.org/W2058965736","https://openalex.org/W2064741519","https://openalex.org/W2068756725","https://openalex.org/W2074630245","https://openalex.org/W2090089568","https://openalex.org/W2092466978","https://openalex.org/W2096451472","https://openalex.org/W2103959632","https://openalex.org/W2108033144","https://openalex.org/W2113584252","https://openalex.org/W2117812871","https://openalex.org/W2117897510","https://openalex.org/W2121078958","https://openalex.org/W2128529555","https://openalex.org/W2132425109","https://openalex.org/W2133772980","https://openalex.org/W2135046866","https://openalex.org/W2140509289","https://openalex.org/W2144396081","https://openalex.org/W2147813562","https://openalex.org/W2148603752","https://openalex.org/W2153635508","https://openalex.org/W2156145910","https://openalex.org/W2165966284","https://openalex.org/W2166280719","https://openalex.org/W2169070520","https://openalex.org/W2170860445","https://openalex.org/W2296744163","https://openalex.org/W2332738317","https://openalex.org/W2343776707","https://openalex.org/W2397603306","https://openalex.org/W2408761132","https://openalex.org/W2461871226","https://openalex.org/W2604976543","https://openalex.org/W2617136835","https://openalex.org/W2730020078","https://openalex.org/W2780628352","https://openalex.org/W2788731403","https://openalex.org/W2794238513","https://openalex.org/W2808017536","https://openalex.org/W2896866862","https://openalex.org/W2911964244","https://openalex.org/W2962829974","https://openalex.org/W3119651796","https://openalex.org/W3120740533","https://openalex.org/W3145128584","https://openalex.org/W3211391890","https://openalex.org/W4230946174","https://openalex.org/W4246219036","https://openalex.org/W6675836192","https://openalex.org/W6679179291","https://openalex.org/W6681034063","https://openalex.org/W6712154291","https://openalex.org/W6749682106","https://openalex.org/W6752340499"],"related_works":["https://openalex.org/W2161440356","https://openalex.org/W2383335574","https://openalex.org/W1489507320","https://openalex.org/W233771590","https://openalex.org/W2127616648","https://openalex.org/W2348510359","https://openalex.org/W3121830895","https://openalex.org/W2900686919","https://openalex.org/W2047800684","https://openalex.org/W4238478255"],"abstract_inverted_index":{"Fuzzy":[0],"twin":[1,86],"support":[2,66,87,135,203,207],"vector":[3,88,204,208],"machine":[4,9,89],"(FTSVM)":[5],"is":[6,13,95,182,190],"an":[7,73,188],"effective":[8],"learning":[10],"technique":[11,176],"that":[12,77,187],"able":[14,191],"to":[15,97,114,160,192],"overcome":[16],"the":[17,30,32,38,42,52,58,64,79,99,103,124,131,134,149,162,165,171,174,178,201,216],"negative":[18],"impact":[19],"of":[20,34,54,81,126,164],"noise":[21,100],"and":[22,47,61,110,147,154,211],"outliers":[23],"in":[24,37,57,215],"tackling":[25],"data":[26,46,56],"classification":[27,150],"problems.":[28],"In":[29],"FTSVM,":[31,210],"degree":[33],"membership":[35,94],"function":[36],"sample":[39],"space":[40,43,60],"describes":[41],"between":[44],"input":[45,55],"class":[48],"center,":[49],"while":[50],"ignoring":[51],"position":[53],"feature":[59],"simply":[62],"miscalculated":[63],"ledge":[65],"vectors":[67],"as":[68,196],"noises.":[69],"This":[70],"paper":[71],"presents":[72],"intuitionistic":[74,82],"FTSVM":[75],"(IFTSVM)":[76],"combines":[78],"idea":[80],"fuzzy":[83,93,206],"number":[84],"with":[85,177,198],"(TSVM).":[90],"An":[91,119],"adequate":[92],"employed":[96,159],"reduce":[98],"created":[101],"by":[102],"pollutant":[104],"inputs.":[105],"Two":[106,152],"functions,":[107],"i.e.,":[108],"linear":[109],"nonlinear,":[111],"are":[112,158],"used":[113],"formulate":[115],"two":[116],"nonparallel":[117],"hyperplanes.":[118],"IFTSVM":[120,167,189],"not":[121],"only":[122],"reduces":[123],"influence":[125],"noises,":[127],"it":[128],"also":[129],"distinguishes":[130],"noises":[132],"from":[133,200],"vectors.":[136],"Further,":[137],"this":[138],"modification":[139],"can":[140],"minimize":[141],"a":[142],"newly":[143],"formulated":[144],"structural":[145],"risk":[146],"improve":[148],"accuracy.":[151],"artificial":[153],"eleven":[155],"benchmark":[156],"problems":[157],"evaluate":[161],"effectiveness":[163],"proposed":[166],"model.":[168],"To":[169],"quantify":[170],"results":[172,195],"statistically,":[173],"bootstrap":[175],"95%":[179],"confidence":[180],"intervals":[181],"used.":[183],"The":[184],"outcome":[185],"shows":[186],"produce":[193],"promising":[194],"compared":[197],"those":[199],"original":[202],"machine,":[205,209],"other":[212],"models":[213],"reported":[214],"literature.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":44},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":6}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}