{"id":"https://openalex.org/W4401567405","doi":"https://doi.org/10.1109/tits.2024.3440011","title":"Low-Rank Tensor and Hybrid Smoothness Regularization-Based Approach for Traffic Data Imputation With Multimodal Missing","display_name":"Low-Rank Tensor and Hybrid Smoothness Regularization-Based Approach for Traffic Data Imputation With Multimodal Missing","publication_year":2024,"publication_date":"2024-08-14","ids":{"openalex":"https://openalex.org/W4401567405","doi":"https://doi.org/10.1109/tits.2024.3440011"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3440011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3440011","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation 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/A5102965303","display_name":"Zeyu Zeng","orcid":"https://orcid.org/0000-0003-1120-3527"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zeyu Zeng","raw_affiliation_strings":["College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1120-3527","affiliations":[{"raw_affiliation_string":"College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045310328","display_name":"Bin Liu","orcid":"https://orcid.org/0000-0002-7467-2331"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Liu","raw_affiliation_strings":["College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-7467-2331","affiliations":[{"raw_affiliation_string":"College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101417040","display_name":"Jun Feng","orcid":"https://orcid.org/0000-0001-8066-5261"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Feng","raw_affiliation_strings":["College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-8066-5261","affiliations":[{"raw_affiliation_string":"College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102746820","display_name":"Xiaolin Yang","orcid":"https://orcid.org/0000-0002-4243-6430"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Yang","raw_affiliation_strings":["College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Physics and the Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I31595395"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102965303"],"corresponding_institution_ids":["https://openalex.org/I31595395"],"apc_list":null,"apc_paid":null,"fwci":2.7759,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.91958042,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"25","issue":"10","first_page":"13014","last_page":"13026"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9606000185012817,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9569000005722046,"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/imputation","display_name":"Imputation (statistics)","score":0.7353523969650269},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6262187957763672},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5080931186676025},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.4724472165107727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46582266688346863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4344261586666107},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.42925459146499634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3809233605861664},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35175782442092896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2640265226364136},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.08300924301147461},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.0790325403213501}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7353523969650269},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6262187957763672},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5080931186676025},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.4724472165107727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46582266688346863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4344261586666107},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.42925459146499634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3809233605861664},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35175782442092896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2640265226364136},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.08300924301147461},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0790325403213501}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3440011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3440011","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2763516173","display_name":null,"funder_award_id":"scsxdz2021yb02","funder_id":"https://openalex.org/F4320322922","funder_display_name":"Department of Science and Technology of Sichuan Province"},{"id":"https://openalex.org/G614717748","display_name":null,"funder_award_id":"2024NSFSC0083","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"}],"funders":[{"id":"https://openalex.org/F4320322922","display_name":"Department of Science and Technology of Sichuan Province","ror":"https://ror.org/04323m874"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1476376401","https://openalex.org/W1798398164","https://openalex.org/W1908793230","https://openalex.org/W1977146314","https://openalex.org/W1992426838","https://openalex.org/W1999788007","https://openalex.org/W2016670111","https://openalex.org/W2026561823","https://openalex.org/W2030927653","https://openalex.org/W2042048367","https://openalex.org/W2051299429","https://openalex.org/W2064683861","https://openalex.org/W2082533141","https://openalex.org/W2091449379","https://openalex.org/W2096863518","https://openalex.org/W2114933215","https://openalex.org/W2153919224","https://openalex.org/W2163150789","https://openalex.org/W2164278908","https://openalex.org/W2179076887","https://openalex.org/W2327462959","https://openalex.org/W2756203131","https://openalex.org/W2757057438","https://openalex.org/W2762874775","https://openalex.org/W2766804299","https://openalex.org/W2767854248","https://openalex.org/W2792473404","https://openalex.org/W2902048196","https://openalex.org/W2944102862","https://openalex.org/W2963328634","https://openalex.org/W2964214749","https://openalex.org/W2970760100","https://openalex.org/W2979001238","https://openalex.org/W2991063736","https://openalex.org/W2993297185","https://openalex.org/W2997965215","https://openalex.org/W3022425365","https://openalex.org/W3103720336","https://openalex.org/W3166827425","https://openalex.org/W3167202680","https://openalex.org/W3202635391","https://openalex.org/W3206445549","https://openalex.org/W4281257454","https://openalex.org/W4323022420"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"Spatiotemporal":[0],"traffic":[1,11,33,47,65,89,104,114,178],"data":[2,12,48,66,90,115,179],"is":[3,91],"vitally":[4],"important":[5],"in":[6,20,59],"intelligent":[7],"transportation":[8],"systems,":[9],"but":[10],"values":[13],"are":[14],"inevitably":[15],"missing":[16,71,96,168,185],"due":[17,50],"to":[18,46,51,54,94,148],"malfunctions":[19],"sensing":[21],"devices":[22],"or":[23],"transmission":[24],"networks.":[25],"This":[26],"will":[27],"cause":[28],"trouble":[29],"for":[30,84,183],"the":[31,56,60,85,100,108,123,127,130,136,146,151,156],"subsequent":[32],"flow":[34],"prediction":[35],"work.":[36],"Low-rank":[37],"tensor":[38,124],"imputation":[39,49,116,180],"methods":[40],"have":[41],"recently":[42],"received":[43],"increasing":[44],"attention":[45],"their":[52],"ability":[53],"capture":[55],"spatial-temporal":[57],"information":[58],"way":[61],"of":[62,88,103,122],"multi-dimension.":[63],"However,":[64],"often":[67],"encounters":[68],"challenging":[69],"multimodal":[70,167],"scenarios,":[72],"including":[73],"random":[74],"missing,":[75,77],"fiber":[76,184],"and":[78,129,139,154,186],"slice":[79,187],"missing.":[80,188],"Thus,":[81],"only":[82],"accounting":[83],"global":[86,137],"low-rankness":[87,138],"less":[92],"sufficient":[93],"recover":[95],"data.":[97],"Motivated":[98],"by":[99],"local":[101,140],"smoothness":[102,141],"data,":[105],"we":[106,172],"introduce":[107],"hybrid":[109],"total":[110,132],"variation":[111],"into":[112],"spatiotemporal":[113],"framework.":[117],"The":[118],"proposed":[119,152,173],"model":[120,153],"consists":[121],"nuclear":[125],"norm,":[126],"first-order":[128],"second-order":[131],"variation,":[133],"which":[134],"presents":[135],"prior,":[142],"respectively.":[143],"We":[144],"utilize":[145],"ADMM":[147],"effectively":[149],"solve":[150],"establish":[155],"theoretical":[157],"guarantee.":[158],"Numerous":[159],"experiments":[160],"on":[161],"two":[162],"real-world":[163],"datasets":[164],"under":[165],"three":[166],"scenarios":[169],"indicate":[170],"that":[171],"method":[174],"outperforms":[175],"some":[176],"state-of-the-art":[177],"methods,":[181],"especially":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}