{"id":"https://openalex.org/W4417438593","doi":"https://doi.org/10.1109/jiot.2025.3645316","title":"Spatio-Temporal Propagation-Aware Graph Neural Network for Traffic Flow Prediction","display_name":"Spatio-Temporal Propagation-Aware Graph Neural Network for Traffic Flow Prediction","publication_year":2025,"publication_date":"2025-12-17","ids":{"openalex":"https://openalex.org/W4417438593","doi":"https://doi.org/10.1109/jiot.2025.3645316"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2025.3645316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3645316","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/A5002541175","display_name":"Wenbiao Yang","orcid":"https://orcid.org/0000-0001-8320-0988"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenbiao Yang","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016584004","display_name":"Wenli Shang","orcid":"https://orcid.org/0000-0001-6022-5381"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenli Shang","raw_affiliation_strings":["School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062494507","display_name":"Zhiquan Liu","orcid":"https://orcid.org/0000-0002-3934-2177"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiquan Liu","raw_affiliation_strings":["College of Cyber Security, Jinan University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Cyber Security, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002541175"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45914138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"5","first_page":"9575","last_page":"9589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9646000266075134,"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":0.9646000266075134,"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":0.00860000029206276,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.005799999926239252,"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/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5638999938964844},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5464000105857849},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4683000147342682},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44020000100135803},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.36660000681877136},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.3465000092983246},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.3452000021934509},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.34130001068115234}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.777400016784668},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5638999938964844},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5464000105857849},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4683000147342682},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44020000100135803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.375900000333786},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3555999994277954},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.3465000092983246},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.3452000021934509},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C27458966","wikidata":"https://www.wikidata.org/wiki/Q1187693","display_name":"Control flow graph","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3330000042915344},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3158000111579895},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.2921999990940094},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27079999446868896},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3645316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3645316","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Traffic":[0],"flow":[1],"prediction":[2],"is":[3],"fundamental":[4],"to":[5],"intelligent":[6],"transportation":[7,117],"systems,":[8],"requiring":[9],"accurate":[10],"modeling":[11],"of":[12,22],"complex":[13],"spatio-temporal":[14],"dependencies.":[15],"Existing":[16],"methods":[17],"typically":[18],"assume":[19],"instantaneous":[20],"propagation":[21,43,60,114],"traffic":[23,46,113],"conditions,":[24],"ignoring":[25],"inherent":[26],"time":[27],"delays":[28,44,61],"in":[29,45],"real-world":[30,92],"systems.":[31],"We":[32],"propose":[33],"STPAGNN":[34],"(Spatio-Temporal":[35],"Propagation-Aware":[36,66],"Graph":[37,68],"Neural":[38],"Network),":[39],"which":[40],"explicitly":[41],"models":[42],"networks.":[47],"Our":[48],"approach":[49],"introduces":[50],"three":[51],"innovations:":[52],"(1)":[53],"Delay-Aware":[54],"Temporal":[55],"Identity":[56],"Embedding":[57],"(DATIE)":[58],"incorporating":[59],"into":[62,112],"temporal":[63],"patterns,":[64],"(2)":[65],"Dynamic":[67],"Learning":[69],"(PADGL)":[70],"updating":[71],"graph":[72],"structures":[73],"with":[74,97],"transmission":[75],"delays,":[76],"and":[77,100],"(3)":[78],"Multi-Delay":[79],"Multi-Scale":[80],"Interaction":[81],"Module":[82],"(MDMIM)":[83],"capturing":[84],"interactions":[85],"across":[86],"delay":[87],"horizons.":[88],"Experiments":[89],"on":[90],"four":[91],"datasets":[93],"demonstrate":[94],"state-of-the-art":[95],"performance":[96],"8.2%":[98],"MAE":[99],"7.5%":[101],"RMSE":[102],"improvements":[103],"over":[104],"existing":[105],"methods.":[106],"The":[107],"model":[108],"provides":[109],"interpretable":[110],"insights":[111],"patterns":[115],"for":[116],"management":[118],"applications.":[119]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-17T00:00:00"}