{"id":"https://openalex.org/W4404370740","doi":"https://doi.org/10.1109/tfuzz.2024.3497974","title":"Multivariate Long-Term Forecasting Using Multilinear Trend Fuzzy Information Granules for Traffic Time Series","display_name":"Multivariate Long-Term Forecasting Using Multilinear Trend Fuzzy Information Granules for Traffic Time Series","publication_year":2024,"publication_date":"2024-11-14","ids":{"openalex":"https://openalex.org/W4404370740","doi":"https://doi.org/10.1109/tfuzz.2024.3497974"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2024.3497974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3497974","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/A5100620044","display_name":"Xianfeng Huang","orcid":"https://orcid.org/0000-0001-8933-6907"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianfeng Huang","raw_affiliation_strings":["School of Economics and Management, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8933-6907","affiliations":[{"raw_affiliation_string":"School of Economics and Management, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhiyuan Huang","orcid":"https://orcid.org/0000-0003-1284-2128"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Huang","raw_affiliation_strings":["School of Economics and Management, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1284-2128","affiliations":[{"raw_affiliation_string":"School of Economics and Management, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100691996","display_name":"Jianming Zhan","orcid":"https://orcid.org/0000-0003-2510-9515"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianming Zhan","raw_affiliation_strings":["School of Mathematics and Statistics, Hubei Minzu University, Enshi, China"],"raw_orcid":"https://orcid.org/0000-0003-2510-9515","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Hubei Minzu University, Enshi, China","institution_ids":["https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1704,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.9285976,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"33","issue":"3","first_page":"932","last_page":"946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9429000020027161,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9244999885559082,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.682546854019165},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6513972878456116},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6128193736076355},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5820760726928711},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5756359696388245},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.49324482679367065},{"id":"https://openalex.org/keywords/long-term-prediction","display_name":"Long-term prediction","score":0.47577252984046936},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.382712185382843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3710295855998993},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2811310887336731}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.682546854019165},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6513972878456116},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6128193736076355},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5820760726928711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5756359696388245},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.49324482679367065},{"id":"https://openalex.org/C2776537626","wikidata":"https://www.wikidata.org/wiki/Q4047883","display_name":"Long-term prediction","level":2,"score":0.47577252984046936},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.382712185382843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3710295855998993},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2811310887336731},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2024.3497974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3497974","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":[{"score":0.5899999737739563,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G1362002787","display_name":null,"funder_award_id":"12271146","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4288520214","display_name":null,"funder_award_id":"72301195","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W2036785686","https://openalex.org/W2037250283","https://openalex.org/W2089700840","https://openalex.org/W2089717797","https://openalex.org/W2128160875","https://openalex.org/W2157423047","https://openalex.org/W2177262641","https://openalex.org/W2550257869","https://openalex.org/W2573137292","https://openalex.org/W2777680782","https://openalex.org/W2799109291","https://openalex.org/W2897998689","https://openalex.org/W2905967367","https://openalex.org/W2969296454","https://openalex.org/W2990955039","https://openalex.org/W2997546679","https://openalex.org/W2998528699","https://openalex.org/W3134585217","https://openalex.org/W3135400423","https://openalex.org/W3176196442","https://openalex.org/W3189142404","https://openalex.org/W3201019813","https://openalex.org/W4200535448","https://openalex.org/W4206062825","https://openalex.org/W4223926961","https://openalex.org/W4226320832","https://openalex.org/W4280592664","https://openalex.org/W4285132771","https://openalex.org/W4285157836","https://openalex.org/W4304776921","https://openalex.org/W4313004671","https://openalex.org/W4313577291","https://openalex.org/W4319019488","https://openalex.org/W4322755838","https://openalex.org/W4361002120","https://openalex.org/W4361018931","https://openalex.org/W4363649763","https://openalex.org/W4378697336","https://openalex.org/W4378978063","https://openalex.org/W4382203079","https://openalex.org/W4383551049","https://openalex.org/W4385285268","https://openalex.org/W4385756462","https://openalex.org/W4390610528","https://openalex.org/W4392883897","https://openalex.org/W4394687230","https://openalex.org/W4395447244","https://openalex.org/W6852840396"],"related_works":["https://openalex.org/W2118640767","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660","https://openalex.org/W2162883116","https://openalex.org/W2325790386","https://openalex.org/W2015977711","https://openalex.org/W2375884488","https://openalex.org/W2245945741"],"abstract_inverted_index":{"Long-term":[0],"forecasting":[1,55,67,80,145,187],"for":[2,30,107,147],"time":[3,44,117,121,133,149,165],"series":[4,118,166,172],"is":[5,24],"gaining":[6],"significant":[7],"attention":[8],"in":[9],"many":[10],"emerging":[11],"fields,":[12],"such":[13],"as":[14],"machine":[15],"learning":[16],"and":[17,27,73,103,162,176,192],"artificial":[18],"intelligence.":[19],"Linear":[20],"fuzzy":[21,70,90],"information":[22,71,91,106],"granulation":[23,92],"a":[25,63,78,87,95,125,143],"well-recognized":[26],"powerful":[28],"tool":[29],"long-term":[31,65,144],"forecasting.":[32],"However,":[33],"existing":[34],"studies":[35],"on":[36,182],"this":[37,58,60,138,152],"topic":[38],"have":[39],"been":[40],"restricted":[41],"to":[42,77],"univariate":[43],"series,":[45],"falling":[46],"short":[47],"of":[48,53,114,173,194],"meeting":[49],"the":[50,112,115,131,157,170,177,190],"real-world":[51,184],"demands":[52],"complex":[54],"issues.":[56],"In":[57],"regard,":[59],"article":[61],"proposes":[62],"multivariate":[64,148],"time-series":[66,105],"model":[68,83,141],"using":[69],"granules":[72],"demonstrates":[74,189],"its":[75],"application":[76],"transportation":[79],"task.":[81],"Our":[82],"begins":[84],"by":[85],"designing":[86],"multilinear":[88],"trend":[89],"scheme":[93,100],"within":[94,119],"justifiable":[96],"granularity":[97],"framework.":[98],"This":[99],"effectively":[101],"granulates":[102],"delineates":[104],"each":[108,120],"feature.":[109,179],"To":[110],"ensure":[111],"normalization":[113],"granular":[116,164,171],"window,":[122],"we":[123],"propose":[124],"scale":[126],"equalization":[127],"strategy":[128],"that":[129],"leverages":[130],"dynamic":[132],"warping":[134],"algorithm.":[135],"Building":[136],"upon":[137],"foundation,":[139],"our":[140,195],"introduces":[142],"mechanism":[146,153],"series.":[150],"Notably,":[151],"fosters":[154],"interconnections,":[155],"bridging":[156],"temporal":[158],"gap":[159],"between":[160],"past":[161],"future":[163],"while":[167],"concurrently":[168],"linking":[169],"influential":[174],"features":[175],"target":[178],"Empirical":[180],"validation":[181],"six":[183],"traffic":[185],"flow":[186],"datasets":[188],"effectiveness":[191],"competitiveness":[193],"proposed":[196],"model.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":4}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}