{"id":"https://openalex.org/W3111366854","doi":"https://doi.org/10.1109/tfuzz.2020.3044236","title":"The Extreme Value Evolving Predictor","display_name":"The Extreme Value Evolving Predictor","publication_year":2020,"publication_date":"2020-12-11","ids":{"openalex":"https://openalex.org/W3111366854","doi":"https://doi.org/10.1109/tfuzz.2020.3044236","mag":"3111366854"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2020.3044236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2020.3044236","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/A5008133189","display_name":"Amanda O. C. Ayres","orcid":"https://orcid.org/0000-0002-6588-1940"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Amanda O. C. Ayres","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-6588-1940","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035858702","display_name":"Fernando J. Von Zuben","orcid":"https://orcid.org/0000-0002-4128-5415"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fernando J. Von Zuben","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-4128-5415","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":null,"apc_paid":null,"fwci":0.5215,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7397397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"30","issue":"3","first_page":"663","last_page":"675"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9980000257492065,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9980000257492065,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9979000091552734,"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":0.9887999892234802,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.6102100610733032},{"id":"https://openalex.org/keywords/antecedent","display_name":"Antecedent (behavioral psychology)","score":0.5947719216346741},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.588463544845581},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5647162795066833},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5382947325706482},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5215670466423035},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5009548664093018},{"id":"https://openalex.org/keywords/fuzzy-rule","display_name":"Fuzzy rule","score":0.4696107506752014},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.42172205448150635},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36829873919487}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6102100610733032},{"id":"https://openalex.org/C2781256819","wikidata":"https://www.wikidata.org/wiki/Q16828835","display_name":"Antecedent (behavioral psychology)","level":2,"score":0.5947719216346741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.588463544845581},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5647162795066833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5382947325706482},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5215670466423035},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5009548664093018},{"id":"https://openalex.org/C2780049643","wikidata":"https://www.wikidata.org/wiki/Q5511139","display_name":"Fuzzy rule","level":4,"score":0.4696107506752014},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.42172205448150635},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36829873919487},{"id":"https://openalex.org/C138496976","wikidata":"https://www.wikidata.org/wiki/Q175002","display_name":"Developmental psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2020.3044236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2020.3044236","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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W343727706","https://openalex.org/W572355794","https://openalex.org/W843185653","https://openalex.org/W1500657154","https://openalex.org/W1974758710","https://openalex.org/W2018359669","https://openalex.org/W2021347076","https://openalex.org/W2022443690","https://openalex.org/W2027101567","https://openalex.org/W2043637184","https://openalex.org/W2052201135","https://openalex.org/W2052345845","https://openalex.org/W2057974719","https://openalex.org/W2079325629","https://openalex.org/W2081717961","https://openalex.org/W2088866250","https://openalex.org/W2093768254","https://openalex.org/W2097973719","https://openalex.org/W2100332042","https://openalex.org/W2127961257","https://openalex.org/W2129013743","https://openalex.org/W2132093718","https://openalex.org/W2136340804","https://openalex.org/W2151863350","https://openalex.org/W2152161790","https://openalex.org/W2156601771","https://openalex.org/W2162635690","https://openalex.org/W2169934749","https://openalex.org/W2215168096","https://openalex.org/W2266565428","https://openalex.org/W2511274580","https://openalex.org/W2626159553","https://openalex.org/W2698658463","https://openalex.org/W2756444473","https://openalex.org/W2760877408","https://openalex.org/W2766425260","https://openalex.org/W2779495751","https://openalex.org/W2783998967","https://openalex.org/W2896341873","https://openalex.org/W2904795343","https://openalex.org/W2929291387","https://openalex.org/W2936995161","https://openalex.org/W2949676527","https://openalex.org/W2964337638","https://openalex.org/W2965794323","https://openalex.org/W2967930848","https://openalex.org/W2967987700","https://openalex.org/W2970132878","https://openalex.org/W2981790028","https://openalex.org/W3081994904","https://openalex.org/W3168008646","https://openalex.org/W4250364582","https://openalex.org/W4255240758","https://openalex.org/W6761030284"],"related_works":["https://openalex.org/W1719987419","https://openalex.org/W2883667364","https://openalex.org/W1123195735","https://openalex.org/W2196728100","https://openalex.org/W2124296288","https://openalex.org/W2117204475","https://openalex.org/W2097335998","https://openalex.org/W3181753003","https://openalex.org/W1991172126","https://openalex.org/W1983088179"],"abstract_inverted_index":{"This":[0],"article":[1],"introduces":[2],"a":[3,20,99,103],"new":[4],"evolving":[5,15,27,42,125,162],"fuzzy-rule-based":[6],"algorithm":[7,88],"for":[8],"online":[9],"data":[10],"streams,":[11],"named":[12],"extreme":[13,56],"value":[14,57],"predictor":[16],"(EVeP).":[17],"It":[18],"offers":[19],"statistically":[21],"well-founded":[22],"approach":[23],"to":[24,46,150,159],"define":[25],"the":[26,32,35,39,55,60,64,68,71,75,78,82,85,87,90,108,114,120,124,129,133,151,160],"fuzzy":[28,43,104,126],"granules":[29,44,127],"that":[30],"form":[31],"antecedent":[33,130],"and":[34,131,145],"consequent":[36,83,134],"parts":[37,135],"of":[38,63,70,77,84,94,123,136,155],"rules.":[40,109,139],"The":[41,110],"correspond":[45],"radial":[47],"inclusion":[48],"Weibull":[49],"functions.":[50],"They":[51],"are":[52],"interpreted":[53],"by":[54,97,119],"theory":[58],"as":[59],"limiting":[61],"distribution":[62],"relative":[65],"proximity":[66],"among":[67,107,113],"rules":[69,115],"learning":[72,96],"model.":[73],"Regarding":[74],"parameters":[76],"Takagi\u2013Sugeno":[79],"term":[80],"at":[81,128,132],"rules,":[86],"enhances":[89],"already":[91],"demonstrated":[92],"benefits":[93],"multitask":[95],"replacing":[98],"binary":[100],"version":[101],"with":[102],"structural":[105],"relationship":[106],"pairwise":[111],"similarity":[112],"is":[116],"automatically":[117],"provided":[118],"current":[121],"interaction":[122],"their":[137],"corresponding":[138],"Several":[140],"computational":[141],"experiments,":[142],"using":[143],"artificial":[144],"real-world":[146],"time":[147],"series,":[148],"attest":[149],"dominating":[152],"prediction":[153],"performance":[154],"EVeP":[156],"when":[157],"compared":[158],"state-of-the-art":[161],"algorithms.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}