{"id":"https://openalex.org/W4406522576","doi":"https://doi.org/10.1109/tits.2025.3527019","title":"The Impact of Network Indices Integration on Traffic Flow Imputation Accuracy: A Machine Learning Approach","display_name":"The Impact of Network Indices Integration on Traffic Flow Imputation Accuracy: A Machine Learning Approach","publication_year":2025,"publication_date":"2025-01-17","ids":{"openalex":"https://openalex.org/W4406522576","doi":"https://doi.org/10.1109/tits.2025.3527019"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3527019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3527019","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/A5029754299","display_name":"Sina Sabzekar","orcid":"https://orcid.org/0000-0001-8368-2307"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Sina Sabzekar","raw_affiliation_strings":["Department of Civil Engineering, Sharif University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093818604","display_name":"Asal Roudbari","orcid":null},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Asal Roudbari","raw_affiliation_strings":["Electrical Engineering Department, Sharif University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061645475","display_name":"Arash Dehghani","orcid":null},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Arash Dehghani","raw_affiliation_strings":["Electrical Engineering Department, Sharif University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115920559","display_name":"Artin Safaeiestalkhzir","orcid":null},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Artin Safaeiestalkhzir","raw_affiliation_strings":["Electrical Engineering Department, Sharif University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003148168","display_name":"Zohreh Amini","orcid":"https://orcid.org/0000-0002-0440-6660"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Zahra Amini","raw_affiliation_strings":["Department of Civil Engineering, Sharif University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029754299"],"corresponding_institution_ids":["https://openalex.org/I133529467"],"apc_list":null,"apc_paid":null,"fwci":4.7629,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.93558127,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"26","issue":"4","first_page":"5411","last_page":"5421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.996999979019165,"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":0.996999979019165,"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/T10524","display_name":"Traffic control and management","score":0.9520999789237976,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9419000148773193,"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/computer-science","display_name":"Computer science","score":0.6386856436729431},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.503034770488739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.502572774887085},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.463955819606781},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4247582256793976},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15154513716697693},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.10635441541671753}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6386856436729431},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.503034770488739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.502572774887085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.463955819606781},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4247582256793976},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15154513716697693},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.10635441541671753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3527019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3527019","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W804139766","https://openalex.org/W1572955664","https://openalex.org/W1620005141","https://openalex.org/W1971937094","https://openalex.org/W1978305832","https://openalex.org/W1979646154","https://openalex.org/W2004824191","https://openalex.org/W2022218646","https://openalex.org/W2023988450","https://openalex.org/W2025844353","https://openalex.org/W2026417691","https://openalex.org/W2039417141","https://openalex.org/W2040292168","https://openalex.org/W2056944867","https://openalex.org/W2074436399","https://openalex.org/W2086799036","https://openalex.org/W2087609307","https://openalex.org/W2091560152","https://openalex.org/W2134784378","https://openalex.org/W2152255412","https://openalex.org/W2153154621","https://openalex.org/W2165992156","https://openalex.org/W2572939427","https://openalex.org/W2758668480","https://openalex.org/W2789443491","https://openalex.org/W2808319310","https://openalex.org/W2899300491","https://openalex.org/W2902048196","https://openalex.org/W2918580218","https://openalex.org/W2950742983","https://openalex.org/W2955819484","https://openalex.org/W2964015378","https://openalex.org/W2965092899","https://openalex.org/W2986055092","https://openalex.org/W2986520817","https://openalex.org/W3037624214","https://openalex.org/W3039638631","https://openalex.org/W3042710080","https://openalex.org/W3045892380","https://openalex.org/W3048452403","https://openalex.org/W3049554854","https://openalex.org/W3123909522","https://openalex.org/W3170708168","https://openalex.org/W4213120921","https://openalex.org/W4213130097","https://openalex.org/W4232323869","https://openalex.org/W4286610775","https://openalex.org/W4313378981","https://openalex.org/W4324292640","https://openalex.org/W4324369021","https://openalex.org/W4327571602","https://openalex.org/W4372215785","https://openalex.org/W4387368875","https://openalex.org/W4387527499","https://openalex.org/W4399623528","https://openalex.org/W4405212311","https://openalex.org/W6679762769","https://openalex.org/W6733620537","https://openalex.org/W6754573523","https://openalex.org/W6756248755","https://openalex.org/W6848781055","https://openalex.org/W6858961115"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,7,42,82,124],"imputation":[2,191],"aims":[3],"to":[4,21,73,76,111,227],"estimate":[5,121],"missing":[6,122,177],"values":[8],"within":[9],"a":[10,107],"traffic":[11,41,81,123,164],"network.":[12],"While":[13],"machine":[14,135,184],"learning":[15,136,139,185],"methods":[16],"have":[17],"been":[18],"widely":[19],"applied":[20],"this":[22],"challenge":[23],"and":[24,51,95,137,150,172,174,222,249],"outperformed":[25],"conventional":[26],"approaches,":[27],"the":[28,33,62,78,92,127,201,233],"current":[29],"literature":[30],"must":[31],"explore":[32],"potential":[34],"benefits":[35],"of":[36,80,157,238,253],"integrating":[37],"network":[38,69,89,196,254],"indices":[39,45,70,90],"into":[40,61,246],"imputation.":[43,83],"Network":[44,148,153],"encompass":[46],"attributes":[47],"associated":[48],"with":[49,166,195,210,213,217,220,224],"nodes":[50],"links,":[52],"such":[53],"as":[54,232],"centrality":[55],"measures,":[56],"which":[57],"provide":[58],"valuable":[59],"insights":[60],"network\u2019s":[63],"structure.":[64],"This":[65],"study":[66,241],"proposes":[67],"adopting":[68],"in":[71,190,236],"addition":[72],"link":[74,102,230],"features":[75],"enhance":[77],"accuracy":[79,192],"Our":[84,240],"proposed":[85,128,160,205],"feature":[86,129,234,247],"set":[87,130],"incorporates":[88],"from":[91],"original":[93],"graph":[94,98],"its":[96],"line":[97],"transformation,":[99],"alongside":[100],"inherent":[101],"features.":[103,119],"Subsequently,":[104],"we":[105],"employ":[106],"correlation":[108],"matrix":[109],"analysis":[110,252],"discern":[112],"relationships":[113],"between":[114],"features,":[115],"thus":[116],"excluding":[117],"dependent":[118],"We":[120],"based":[125],"on":[126,200],"by":[131,208],"utilizing":[132],"five":[133],"state-of-the-art":[134],"deep":[138],"methods,":[140],"including":[141],"KNN,":[142,211],"Random":[143,214],"Forest,":[144,215],"XGBoost,":[145,218],"Graph":[146,151],"Convolutional":[147],"(GCN),":[149],"Attention":[152],"(GAT).":[154],"The":[155],"results":[156],"testing":[158],"our":[159,204],"method":[161,186],"across":[162],"various":[163],"networks":[165],"varying":[167],"sizes":[168],"(Sioux":[169],"Falls,":[170],"Anaheim,":[171],"Chicago)":[173],"under":[175],"different":[176],"rates":[178],"(0.1-0.9)":[179],"consistently":[180],"demonstrate":[181],"that":[182],"each":[183],"experiences":[187],"an":[188],"improvement":[189],"when":[193],"augmented":[194],"indices.":[197,255],"More":[198],"specifically,":[199],"Anaheim":[202],"dataset,":[203],"approach":[206],"improves":[207],"8.74%":[209],"3.26%":[212],"2.69%":[216],"4.88%":[219],"GCN,":[221],"4.85%":[223],"GAT,":[225],"compared":[226],"using":[228],"only":[229],"properties":[231],"set,":[235],"terms":[237],"PCC.":[239],"also":[242],"includes":[243],"further":[244],"investigations":[245],"importance":[248],"computational":[250],"cost":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
