{"id":"https://openalex.org/W4285179601","doi":"https://doi.org/10.1109/jiot.2022.3172447","title":"A Novel Spatiotemporal Data Low-Rank Imputation Approach for Traffic Sensor Network","display_name":"A Novel Spatiotemporal Data Low-Rank Imputation Approach for Traffic Sensor Network","publication_year":2022,"publication_date":"2022-05-04","ids":{"openalex":"https://openalex.org/W4285179601","doi":"https://doi.org/10.1109/jiot.2022.3172447"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2022.3172447","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2022.3172447","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5100333930","display_name":"Xiaobo Chen","orcid":"https://orcid.org/0000-0001-9940-1637"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobo Chen","raw_affiliation_strings":["School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0001-9940-1637","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108650469","display_name":"Shurong Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shurong Liang","raw_affiliation_strings":["Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361542","display_name":"Zhihao Zhang","orcid":"https://orcid.org/0000-0003-1003-9913"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Zhang","raw_affiliation_strings":["Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079457723","display_name":"Feng Zhao","orcid":"https://orcid.org/0000-0003-2410-435X"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0003-2410-435X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7845,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.90103488,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"9","issue":"20","first_page":"20122","last_page":"20135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994000196456909,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8183630108833313},{"id":"https://openalex.org/keywords/harmony-search","display_name":"Harmony search","score":0.6594434976577759},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6286260485649109},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.5616104602813721},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.40205687284469604},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3594614267349243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33418741822242737},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2947656214237213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8183630108833313},{"id":"https://openalex.org/C33099171","wikidata":"https://www.wikidata.org/wiki/Q26208718","display_name":"Harmony search","level":2,"score":0.6594434976577759},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6286260485649109},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.5616104602813721},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.40205687284469604},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3594614267349243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33418741822242737},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2947656214237213}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2022.3172447","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2022.3172447","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G5285082455","display_name":null,"funder_award_id":"2017-JXQC-007","funder_id":"https://openalex.org/F4320326182","funder_display_name":"Six Talent Peaks Project in Jiangsu Province"},{"id":"https://openalex.org/G5331186488","display_name":null,"funder_award_id":"62176140","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5336214237","display_name":null,"funder_award_id":"61773184","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7378939222","display_name":null,"funder_award_id":"2018YFB0105000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320326182","display_name":"Six Talent Peaks Project in Jiangsu Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1967575164","https://openalex.org/W1983479840","https://openalex.org/W1993885071","https://openalex.org/W2039015671","https://openalex.org/W2064186732","https://openalex.org/W2064675550","https://openalex.org/W2090035883","https://openalex.org/W2091449379","https://openalex.org/W2096863518","https://openalex.org/W2103972604","https://openalex.org/W2114933215","https://openalex.org/W2115098571","https://openalex.org/W2115337059","https://openalex.org/W2125027820","https://openalex.org/W2129131372","https://openalex.org/W2130187411","https://openalex.org/W2162210260","https://openalex.org/W2163150789","https://openalex.org/W2293724770","https://openalex.org/W2343462218","https://openalex.org/W2552480641","https://openalex.org/W2604847698","https://openalex.org/W2605190428","https://openalex.org/W2611328865","https://openalex.org/W2616654950","https://openalex.org/W2726858467","https://openalex.org/W2773306235","https://openalex.org/W2792584708","https://openalex.org/W2799891732","https://openalex.org/W2801457640","https://openalex.org/W2802508687","https://openalex.org/W2889175325","https://openalex.org/W2899300491","https://openalex.org/W2902048196","https://openalex.org/W2926585089","https://openalex.org/W2939939530","https://openalex.org/W2964010366","https://openalex.org/W2991063736","https://openalex.org/W2999732489","https://openalex.org/W3004178587","https://openalex.org/W3034951560","https://openalex.org/W3045435486","https://openalex.org/W3109901740","https://openalex.org/W3137210848","https://openalex.org/W3157605589","https://openalex.org/W3158644168","https://openalex.org/W3166291381","https://openalex.org/W3169524537","https://openalex.org/W4229706427","https://openalex.org/W4244133811","https://openalex.org/W4285147743","https://openalex.org/W4292363360","https://openalex.org/W6603183647","https://openalex.org/W6729542563","https://openalex.org/W6746421562","https://openalex.org/W6751145664"],"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":{"The":[0,172,187],"Internet":[1],"of":[2,40,48,56,117,121],"Things":[3],"(IoT)":[4],"has":[5],"enormous":[6],"potential":[7],"to":[8,103,141,182],"transform":[9],"the":[10,21,37,41,53,86,105,115,135,146,165,184,194,206],"transport":[11],"industry":[12],"by":[13,25,70,133],"improving":[14],"passenger":[15],"experiences,":[16],"safety,":[17],"and":[18,76,198],"efficiency.":[19],"However,":[20],"collected":[22],"spatiotemporal":[23],"data":[24,178],"traffic":[26,177],"sensor":[27],"network":[28],"often":[29],"suffer":[30],"from":[31],"missing":[32],"values":[33],"(MVs),":[34],"which":[35],"affect":[36],"overall":[38],"performance":[39],"system.":[42],"As":[43],"a":[44,65,80],"result,":[45],"accurate":[46],"recovery":[47],"MVs":[49,67],"is":[50,112,160],"essential":[51],"for":[52,99,145],"successful":[54],"application":[55],"IoT":[57],"in":[58,127,139,168,191],"transportation.":[59],"In":[60,83,101],"this":[61],"article,":[62],"we":[63],"propose":[64],"novel":[66],"imputation":[68,207],"model":[69],"integrating":[71],"low-rank":[72],"tensor":[73],"completion":[74,197],"(LRTC)":[75],"sparse":[77],"self-representation":[78],"into":[79],"unified":[81],"framework.":[82],"doing":[84],"so,":[85],"global":[87],"multidimensional":[88],"correlation,":[89],"as":[90,92],"well":[91,97],"sample":[93],"self-similarity,":[94],"can":[95,129],"be":[96,130],"leveraged":[98],"imputation.":[100],"order":[102,140],"solve":[104],"proposed":[106,185],"model,":[107,147],"an":[108,148],"elaborate":[109],"solution":[110],"algorithm":[111,153],"developed,":[113,161],"following":[114],"principle":[116],"alternating":[118],"direction":[119],"method":[120,203],"multipliers":[122],"(ADMMs).":[123],"Importantly,":[124],"each":[125],"step":[126],"ADMM":[128],"implemented":[131],"efficiently":[132],"analyzing":[134],"problem":[136],"structure.":[137],"Moreover,":[138],"select":[142],"proper":[143],"parameters":[144],"improved":[149],"harmony":[150,170],"search":[151],"heuristic":[152],"based":[154],"on":[155,174],"dual":[156],"harmonies":[157],"generation":[158],"strategy":[159],"thus":[162],"sufficiently":[163],"considering":[164],"information":[166],"contained":[167],"current":[169],"memory.":[171],"experiments":[173],"two":[175],"real-world":[176],"are":[179],"carried":[180],"out":[181],"evaluate":[183],"approach.":[186],"results":[188],"verify":[189],"that":[190],"comparison":[192],"with":[193],"classic":[195],"matrix/tensor":[196],"other":[199],"competing":[200],"algorithms,":[201],"our":[202],"significantly":[204],"improves":[205],"performance.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
