{"id":"https://openalex.org/W7161136004","doi":"https://doi.org/10.1109/tfuzz.2026.3693480","title":"Multivariate Prediction Model With Adaptive Kernel Configuration Based on Asymmetric Transfer Entropy and Fuzzy $C$-Means in CNN-Transformer","display_name":"Multivariate Prediction Model With Adaptive Kernel Configuration Based on Asymmetric Transfer Entropy and Fuzzy $C$-Means in CNN-Transformer","publication_year":2026,"publication_date":"2026-05-14","ids":{"openalex":"https://openalex.org/W7161136004","doi":"https://doi.org/10.1109/tfuzz.2026.3693480"},"language":null,"primary_location":{"id":"doi:10.1109/tfuzz.2026.3693480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2026.3693480","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/A5136168910","display_name":"Haonan Hu","orcid":null},"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":"Haonan Hu","raw_affiliation_strings":["School of Mathematics and Statistics, Hubei Minzu University, Enshi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Hubei Minzu University, Enshi, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","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"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136137387","display_name":"Jin Hee Yoon","orcid":null},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin Hee Yoon","raw_affiliation_strings":["Department of Artificial Intelligence and Information Technology, Sejong University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-1437-1350","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Information Technology, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136098784","display_name":"Weiping Ding","orcid":"https://orcid.org/0000-0002-3180-7347"},"institutions":[{"id":"https://openalex.org/I199305430","display_name":"Nantong University","ror":"https://ror.org/02afcvw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I199305430"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiping Ding","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China"],"raw_orcid":"https://orcid.org/0000-0002-3180-7347","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China","institution_ids":["https://openalex.org/I199305430"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.58740829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"7","first_page":"2378","last_page":"2392"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.10040000081062317,"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":0.10040000081062317,"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/T12261","display_name":"Statistical Mechanics and Entropy","score":0.05119999870657921,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13748","display_name":"Advanced Statistical Modeling Techniques","score":0.044599998742341995,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/entropy","display_name":"Entropy (arrow of time)","score":0.536899983882904},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5045999884605408},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44769999384880066},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4415000081062317},{"id":"https://openalex.org/keywords/transfer-function","display_name":"Transfer function","score":0.3578999936580658},{"id":"https://openalex.org/keywords/transfer-entropy","display_name":"Transfer entropy","score":0.35269999504089355}],"concepts":[{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.536899983882904},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5045999884605408},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4562000036239624},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44769999384880066},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4415000081062317},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4401000142097473},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38359999656677246},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C182049051","wikidata":"https://www.wikidata.org/wiki/Q17147155","display_name":"Transfer entropy","level":3,"score":0.35269999504089355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3433000147342682},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.32330000400543213},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2955000102519989},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2651999890804291},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.2630000114440918},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.2621000111103058},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2026.3693480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2026.3693480","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":[{"display_name":"Affordable and clean energy","score":0.4698040187358856,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G5834381768","display_name":null,"funder_award_id":"12471430","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7854009930","display_name":null,"funder_award_id":"12571494","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,6,14,46,147,153],"era":[2],"of":[3,9,16,152,201],"digital":[4],"transformation,":[5],"large-scale":[7],"deployment":[8],"sensors":[10],"has":[11],"led":[12],"to":[13,44,84,129,144,184],"collection":[15],"highly":[17],"complex":[18],"and":[19,108,126,136,150,172,204,212],"diverse":[20],"data,":[21],"posing":[22],"significant":[23],"challenges":[24],"for":[25,95],"multivariate":[26,63],"time":[27],"series":[28],"forecasting":[29,32],"(MTSF).":[30],"Traditional":[31],"approaches,":[33],"often":[34],"based":[35],"on":[36,188],"linear":[37],"assumptions,":[38],"are":[39],"limited":[40],"in":[41,51,133,199,214],"their":[42],"ability":[43,211],"capture":[45],"nonlinear":[47],"temporal":[48],"dynamics":[49],"prevalent":[50],"real-world":[52,190],"scenarios.":[53],"To":[54],"address":[55],"these":[56],"challenges,":[57],"this":[58],"study":[59],"proposes":[60],"an":[61,78],"innovative":[62],"prediction":[64,158,180,202],"framework":[65,76],"that":[66,193],"integrates":[67,168],"deep":[68],"learning":[69,73],"with":[70],"traditional":[71],"machine":[72],"techniques.":[74],"The":[75,165],"incorporates":[77,123],"asymmetric":[79],"transfer":[80],"entropy":[81],"coefficient":[82],"(ATC)":[83],"identify":[85],"genuine":[86],"causal":[87],"relationships":[88,110],"among":[89,111],"features,":[90],"constructing":[91],"a":[92],"directed":[93],"graph":[94],"feature":[96,102,162,169],"importance":[97],"ranking.":[98],"This":[99,178],"mechanism":[100],"enhances":[101],"selection":[103],"by":[104],"capturing":[105],"both":[106],"dynamic":[107],"static":[109],"variables.":[112],"An":[113],"enhanced":[114],"fuzzy":[115],"C-means":[116],"clustering":[117,138],"algorithm,":[118],"SCFCM,":[119],"is":[120,142,182],"introduced,":[121],"which":[122],"cosine":[124],"similarity":[125],"Euclidean":[127],"distance":[128],"improve":[130],"sample":[131],"discriminability":[132],"high-dimensional":[134,217],"spaces":[135],"enhance":[137],"accuracy.":[139],"Bayesian":[140],"optimization":[141],"employed":[143],"dynamically":[145],"determine":[146],"kernel":[148],"sizes":[149],"numbers":[151],"CNN-Transformer":[154],"(Convolutional":[155],"neural":[156],"network-Transformer)":[157],"network,":[159],"thereby":[160],"improving":[161],"extraction":[163],"efficiency.":[164],"unified":[166],"architecture":[167],"selection,":[170],"clustering,":[171],"forecasting,":[173],"achieving":[174],"superior":[175],"predictive":[176],"performance.":[177],"comprehensive":[179],"model":[181],"referred":[183],"as":[185],"ATC-SCFCM-DKCNT.":[186],"Experiments":[187],"six":[189],"datasets":[191],"demonstrate":[192],"ATC-SCFCM-DKCNT":[194],"consistently":[195],"outperforms":[196],"state-of-the-art":[197],"methods":[198],"terms":[200],"accuracy":[203],"computational":[205],"efficiency,":[206],"highlighting":[207],"its":[208],"strong":[209],"generalization":[210],"robustness":[213],"handling":[215],"complex,":[216],"data.":[218]},"counts_by_year":[],"updated_date":"2026-07-03T06:15:21.484131","created_date":"2026-05-15T00:00:00"}
