{"id":"https://openalex.org/W4408564767","doi":"https://doi.org/10.1109/tnnls.2025.3548165","title":"A Novel Fusion and Feature Selection Framework for Multisource Time-Series Data Based on Information Entropy","display_name":"A Novel Fusion and Feature Selection Framework for Multisource Time-Series Data Based on Information Entropy","publication_year":2025,"publication_date":"2025-03-18","ids":{"openalex":"https://openalex.org/W4408564767","doi":"https://doi.org/10.1109/tnnls.2025.3548165","pmid":"https://pubmed.ncbi.nlm.nih.gov/40100663"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3548165","doi":"https://doi.org/10.1109/tnnls.2025.3548165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3548165","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-a","doyens","jufo-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","pubmed"],"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/A5103270754","display_name":"Xiuwei Chen","orcid":"https://orcid.org/0000-0003-4609-6514","observed_orcids":["https://orcid.org/0000-0003-4609-6514"]},"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":"Xiuwei Chen","raw_affiliation_strings":["School of Mathematics, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-4609-6514","affiliations":[{"raw_affiliation_string":"School of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085723918","display_name":"Li Fang Lai","orcid":"https://orcid.org/0000-0002-7045-0467","observed_orcids":["https://orcid.org/0000-0002-7045-0467"]},"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":"Li Lai","raw_affiliation_strings":["School of Mathematics, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101752471","display_name":"Maokang Luo","orcid":"https://orcid.org/0000-0003-2793-6012","observed_orcids":["https://orcid.org/0000-0003-2793-6012"]},"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":"Maokang Luo","raw_affiliation_strings":["School of Mathematics, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":4.321,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.94814892,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"36","issue":"8","first_page":"15085","last_page":"15095"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.8730000257492065,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.8730000257492065,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.12240000069141388,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/feature-selection","display_name":"feature selection","score":0.9610000252723694},{"id":"https://openalex.org/keywords/rough-set-theory","display_name":"rough set theory","score":0.8790000081062317},{"id":"https://openalex.org/keywords/shannon-entropy","display_name":"Shannon entropy","score":0.9919999837875366},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"dimensionality reduction","score":0.796999990940094},{"id":"https://openalex.org/keywords/redundant-feature-removal","display_name":"redundant feature removal","score":0.7099999785423279},{"id":"https://openalex.org/keywords/source-selection","display_name":"source selection","score":0.5789999961853027},{"id":"https://openalex.org/keywords/classification-accuracy","display_name":"classification accuracy","score":0.8019999861717224}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6436548233032227},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5749476552009583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5680786371231079},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5647003650665283},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5239750742912292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4395335614681244},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4134986698627472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4037459194660187},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07348215579986572},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06767740845680237},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3548165","doi":"https://doi.org/10.1109/tnnls.2025.3548165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3548165","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-a","doyens","jufo-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40100663","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40100663","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1995875735","https://openalex.org/W2059429344","https://openalex.org/W2064675550","https://openalex.org/W2158633287","https://openalex.org/W2166547175","https://openalex.org/W2506225748","https://openalex.org/W2762194741","https://openalex.org/W2769355717","https://openalex.org/W2912622511","https://openalex.org/W2974996171","https://openalex.org/W3005260659","https://openalex.org/W3044203778","https://openalex.org/W3101245099","https://openalex.org/W3123798230","https://openalex.org/W3173539742","https://openalex.org/W3202620420","https://openalex.org/W3210485020","https://openalex.org/W3212203443","https://openalex.org/W4255833381","https://openalex.org/W4280630615","https://openalex.org/W4282980313","https://openalex.org/W4283394375","https://openalex.org/W4283823780","https://openalex.org/W4285038805","https://openalex.org/W4289792606","https://openalex.org/W4312704807","https://openalex.org/W4313123991","https://openalex.org/W4316660799","https://openalex.org/W4366083559","https://openalex.org/W4367599410","https://openalex.org/W4381951318","https://openalex.org/W4382203079","https://openalex.org/W4386243689","https://openalex.org/W4387020117","https://openalex.org/W4388571776","https://openalex.org/W4392948950","https://openalex.org/W4395028148","https://openalex.org/W4396708177","https://openalex.org/W4400033563","https://openalex.org/W4402979097","https://openalex.org/W4413054246","https://openalex.org/W6846825190"],"related_works":["https://openalex.org/W1919101720","https://openalex.org/W4205762803","https://openalex.org/W4390822878","https://openalex.org/W4246257243","https://openalex.org/W2535856026","https://openalex.org/W2265065644","https://openalex.org/W96888382","https://openalex.org/W4386126592","https://openalex.org/W2041308758","https://openalex.org/W4308273529"],"abstract_inverted_index":{"Information":[0],"technology":[1],"growth":[2],"brings":[3],"vast":[4],"time-series":[5,16,37,56,117],"data.":[6,57],"Despite":[7],"richness,":[8],"challenges":[9],"like":[10],"redundancy":[11],"emphasize":[12],"the":[13,43,69,94,105,114],"need":[14],"for":[15,26,54],"data":[17,38,118,130],"fusion":[18,49,70,119],"research.":[19],"Rough":[20],"set":[21,122],"theory,":[22,123],"a":[23,48,73,82],"valuable":[24],"tool":[25],"dealing":[27],"with":[28],"uncertainty,":[29],"can":[30],"identify":[31],"features":[32],"and":[33,50,127,132],"reduce":[34],"dimensionality,":[35],"enhancing":[36,104],"fusion.":[39],"The":[40],"contribution":[41],"of":[42,103,107,116],"study":[44],"lies":[45],"in":[46,85,101,120,129],"establishing":[47],"feature":[51,74],"selection":[52,75],"framework":[53,59],"multisource":[55],"This":[58,110],"selects":[60],"optimal":[61],"information":[62],"sources":[63],"by":[64],"minimizing":[65],"entropy.":[66,86],"In":[67],"addition,":[68],"process":[71],"integrates":[72],"algorithm":[76],"to":[77],"eliminate":[78],"redundant":[79],"features,":[80],"preventing":[81],"sequential":[83],"increase":[84],"Crucial":[87],"experiments":[88],"on":[89],"abundant":[90],"datasets":[91],"demonstrate":[92],"that":[93],"proposed":[95],"approach":[96],"outperforms":[97],"several":[98],"state-of-the-art":[99],"algorithms":[100],"terms":[102],"accuracy":[106,126],"common":[108],"classifiers.":[109],"research":[111],"significantly":[112],"advances":[113],"field":[115],"rough":[121],"offering":[124],"improved":[125],"efficiency":[128],"processing":[131],"analysis.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}