{"id":"https://openalex.org/W4412836765","doi":"https://doi.org/10.1109/tetci.2025.3592260","title":"A Variable-Type Fuzzy System Approach Based on High-Confidence Pseudo-Labels for Semi-Supervised Regression","display_name":"A Variable-Type Fuzzy System Approach Based on High-Confidence Pseudo-Labels for Semi-Supervised Regression","publication_year":2025,"publication_date":"2025-08-01","ids":{"openalex":"https://openalex.org/W4412836765","doi":"https://doi.org/10.1109/tetci.2025.3592260"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2025.3592260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3592260","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","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/A5007551611","display_name":"Tao Zhao","orcid":"https://orcid.org/0000-0001-5127-5301"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Zhao","raw_affiliation_strings":["College of Electrical Engineering, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112972946","display_name":"Kaijie Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kehao Wen","raw_affiliation_strings":["College of Electrical Engineering, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007551611"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10430598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"1","first_page":"519","last_page":"530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9708999991416931,"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":0.9708999991416931,"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":0.92330002784729,"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/variable","display_name":"Variable (mathematics)","score":0.5622138381004333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5445208549499512},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5348127484321594},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.485942006111145},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4669564664363861},{"id":"https://openalex.org/keywords/type","display_name":"Type (biology)","score":0.4563697874546051},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.43543797731399536},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40487322211265564},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3707062602043152},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3147321939468384},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07492238283157349}],"concepts":[{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5622138381004333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5445208549499512},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5348127484321594},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.485942006111145},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4669564664363861},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.4563697874546051},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.43543797731399536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40487322211265564},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3707062602043152},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3147321939468384},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07492238283157349},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2025.3592260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3592260","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G7475274328","display_name":null,"funder_award_id":"62473273","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2044774029","https://openalex.org/W2076414618","https://openalex.org/W2091642480","https://openalex.org/W2103232511","https://openalex.org/W2511274580","https://openalex.org/W2964159205","https://openalex.org/W2967930848","https://openalex.org/W2984221099","https://openalex.org/W2995808743","https://openalex.org/W3001257018","https://openalex.org/W3011325431","https://openalex.org/W3025437210","https://openalex.org/W3109678027","https://openalex.org/W3132834202","https://openalex.org/W3133744637","https://openalex.org/W3151773539","https://openalex.org/W3192311699","https://openalex.org/W3215985540","https://openalex.org/W4221148424","https://openalex.org/W4280488706","https://openalex.org/W4289792623","https://openalex.org/W4312204877","https://openalex.org/W4312505391","https://openalex.org/W4362496230","https://openalex.org/W4377030841","https://openalex.org/W4392908044","https://openalex.org/W4394688053","https://openalex.org/W4400363791"],"related_works":["https://openalex.org/W2349966087","https://openalex.org/W2380341745","https://openalex.org/W2362588090","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808"],"abstract_inverted_index":{"With":[0],"the":[1,63,67,79,91,103,114,119,134,144,151,172,176,180],"increasing":[2,16],"difficulty":[3],"of":[4,25,62,82,93,122,146,153,166],"obtaining":[5],"high-quality":[6],"labeled":[7],"data,":[8,155],"research":[9],"on":[10,46,74,86,118,150,171],"semi-supervised":[11,162],"learning":[12],"algorithms":[13],"has":[14],"received":[15],"attention":[17],"in":[18,99,161],"recent":[19],"years.":[20],"However,":[21],"a":[22,40,127],"large":[23],"amount":[24],"unlabeled":[26,71,154],"data":[27],"leads":[28],"to":[29,34,51,69],"significant":[30],"uncertainty.":[31],"In":[32],"response":[33],"this":[35,37],"challenge,":[36],"article":[38],"proposes":[39],"variable-type":[41],"fuzzy":[42,147],"system":[43,65],"method":[44,135,181],"based":[45,73,85,117,149],"high-confidence":[47],"pseudo":[48,83,97,123],"labels,":[49,124],"aiming":[50],"overcome":[52],"model":[53],"errors":[54],"caused":[55],"by":[56],"uncertainty":[57,160],"effectively.":[58],"A":[59,164],"vital":[60],"feature":[61],"proposed":[64,104,173],"is":[66],"ability":[68],"predict":[70],"samples":[72],"neighborhood":[75],"information":[76],"and":[77,96,111,175],"calculate":[78],"confidence":[80,120],"level":[81,121],"labels":[84,95,98],"similarity.":[87],"To":[88],"better":[89],"reflect":[90],"roles":[92],"real":[94],"constructing":[100,126],"prediction":[101,130],"systems,":[102],"loss":[105],"function":[106],"comprehensively":[107],"considers":[108],"both":[109],"contributions":[110],"dynamically":[112,142],"adjusts":[113],"training":[115],"weights":[116],"thus":[125],"more":[128,157],"robust":[129],"system.":[131],"Very":[132],"importantly,":[133],"introduces":[136],"an":[137],"adaptive":[138],"mechanism":[139],"that":[140,179],"can":[141],"adjust":[143],"type":[145],"set":[148],"proportion":[152],"thereby":[156],"effectively":[158],"handling":[159],"learning.":[163],"series":[165],"accuracy":[167],"tests":[168],"are":[169],"conducted":[170],"method,":[174],"results":[177],"show":[178],"performs":[182],"well.":[183]},"counts_by_year":[],"updated_date":"2026-01-26T23:06:41.788003","created_date":"2025-10-10T00:00:00"}