{"id":"https://openalex.org/W2897540715","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491483","title":"Fuzzy rule-based modeling for interval-valued time series prediction","display_name":"Fuzzy rule-based modeling for interval-valued time series prediction","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897540715","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491483","mag":"2897540715"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2018.8491483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-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/A5049085341","display_name":"Leandro Maciel","orcid":"https://orcid.org/0000-0002-1900-7179"},"institutions":[{"id":"https://openalex.org/I88273585","display_name":"Universidade Federal de S\u00e3o Paulo","ror":"https://ror.org/02k5swt12","country_code":"BR","type":"education","lineage":["https://openalex.org/I88273585"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Leandro Maciel","raw_affiliation_strings":["S\u00e3o Paulo School of Politics, Economics and Business, Federal University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"S\u00e3o Paulo School of Politics, Economics and Business, Federal University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I88273585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070671093","display_name":"Ros\u00e2ngela Ballini","orcid":"https://orcid.org/0000-0001-6683-4380"},"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":"Rosangela Ballini","raw_affiliation_strings":["Institute of Economics, University of Campinas, S\u00e3o Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Economics, University of Campinas, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049085341"],"corresponding_institution_ids":["https://openalex.org/I88273585"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.11754072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9993000030517578,"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/T10320","display_name":"Neural Networks and Applications","score":0.9993000030517578,"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":0.9962000250816345,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9952999949455261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.6914743185043335},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5609179139137268},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5603851675987244},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.53288733959198},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4782097339630127},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4722634553909302},{"id":"https://openalex.org/keywords/prediction-interval","display_name":"Prediction interval","score":0.46862486004829407},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.45760679244995117},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.442410409450531},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4327836036682129},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4315240681171417},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38967037200927734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.305475115776062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30001047253608704},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2918175756931305},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07464781403541565}],"concepts":[{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6914743185043335},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5609179139137268},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5603851675987244},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.53288733959198},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4782097339630127},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4722634553909302},{"id":"https://openalex.org/C103402496","wikidata":"https://www.wikidata.org/wiki/Q1106171","display_name":"Prediction interval","level":2,"score":0.46862486004829407},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.45760679244995117},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.442410409450531},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4327836036682129},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4315240681171417},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38967037200927734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.305475115776062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30001047253608704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2918175756931305},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07464781403541565},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2018.8491483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323809","display_name":"Minist\u00e9rio da Educa\u00e7\u00e3o","ror":"https://ror.org/04d0xx942"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W608486668","https://openalex.org/W1507872748","https://openalex.org/W1549853718","https://openalex.org/W1832338245","https://openalex.org/W1964257178","https://openalex.org/W1965217418","https://openalex.org/W1970636524","https://openalex.org/W1972966947","https://openalex.org/W1988728273","https://openalex.org/W1994440910","https://openalex.org/W2012822803","https://openalex.org/W2019851168","https://openalex.org/W2026176299","https://openalex.org/W2039480584","https://openalex.org/W2039853520","https://openalex.org/W2040410870","https://openalex.org/W2040579227","https://openalex.org/W2054050358","https://openalex.org/W2060943342","https://openalex.org/W2071300659","https://openalex.org/W2072242542","https://openalex.org/W2073002835","https://openalex.org/W2074972084","https://openalex.org/W2078301133","https://openalex.org/W2079325629","https://openalex.org/W2081522710","https://openalex.org/W2090433565","https://openalex.org/W2093709255","https://openalex.org/W2095182114","https://openalex.org/W2113076747","https://openalex.org/W2119981768","https://openalex.org/W2130426550","https://openalex.org/W2133609334","https://openalex.org/W2151159184","https://openalex.org/W2168175751","https://openalex.org/W2182223804","https://openalex.org/W2188682579","https://openalex.org/W2302056359","https://openalex.org/W2331292321","https://openalex.org/W2336679177","https://openalex.org/W2478038200","https://openalex.org/W2500670671","https://openalex.org/W2519923343","https://openalex.org/W2520231440","https://openalex.org/W2522571449","https://openalex.org/W3124577930","https://openalex.org/W3167732984","https://openalex.org/W6677658268","https://openalex.org/W6681987720","https://openalex.org/W6686913460","https://openalex.org/W7056489716"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W2075234505","https://openalex.org/W1585599148","https://openalex.org/W2063427286","https://openalex.org/W2383710691","https://openalex.org/W2341350566","https://openalex.org/W3126075123","https://openalex.org/W2998804369"],"abstract_inverted_index":{"This":[0],"paper":[1],"suggests":[2],"an":[3],"interval":[4,97],"fuzzy":[5,45,67],"inference":[6],"system":[7],"(iFIS)":[8],"modeling":[9],"approach":[10],"for":[11,71],"interval-valued":[12,58,72,117,139],"time":[13,118],"series":[14,119],"forecasting.":[15],"Interval-valued":[16],"data":[17,27,37,73],"arise":[18],"quite":[19],"naturally":[20],"in":[21,24],"many":[22],"situations":[23],"which":[25,51],"such":[26],"represent":[28],"uncertainty/variability":[29],"or":[30],"when":[31],"comprehensive":[32],"ways":[33],"to":[34,89,95,134],"summarize":[35],"large":[36],"sets":[38],"are":[39,83],"required.":[40],"The":[41,61,125],"method":[42],"comprises":[43],"a":[44,53,66,86,91,128],"rule-based":[46],"framework":[47,55],"with":[48,74,85,120],"affine":[49],"consequents":[50,82],"provides":[52],"(non)linear":[54],"that":[56],"processes":[57],"symbolic":[59,96],"data.":[60,98],"iFIS":[62,99,132],"antecedents":[63],"identification":[64],"uses":[65],"c-means":[68],"clustering":[69],"algorithm":[70],"adaptive":[75],"distances,":[76],"whereas":[77],"parameters":[78],"of":[79,131],"the":[80],"linear":[81,92,121],"estimated":[84],"centre-range":[87],"methodology":[88],"fit":[90],"regression":[93],"model":[94],"forecasting":[100,140],"power,":[101],"measured":[102],"by":[103],"accuracy":[104],"metrics":[105],"and":[106,122,138],"statistical":[107],"tests,":[108],"was":[109],"evaluated":[110],"through":[111],"Monte":[112],"Carlo":[113],"experiments":[114],"using":[115],"synthetic":[116],"chaotic":[123],"dynamics.":[124],"results":[126],"indicate":[127],"superior":[129],"performance":[130],"compared":[133],"traditional":[135],"alternative":[136],"single-valued":[137],"models.":[141]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}