{"id":"https://openalex.org/W4416148856","doi":"https://doi.org/10.1109/access.2025.3632115","title":"ModuNet: A Modulated Graph-Token Network for Spatio-Temporal Traffic Flow Forecasting","display_name":"ModuNet: A Modulated Graph-Token Network for Spatio-Temporal Traffic Flow Forecasting","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416148856","doi":"https://doi.org/10.1109/access.2025.3632115"},"language":null,"primary_location":{"id":"doi:10.1109/access.2025.3632115","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3632115","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3632115","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tianxing Zhang","orcid":"https://orcid.org/0009-0000-7071-5659"},"institutions":[{"id":"https://openalex.org/I4400600914","display_name":"Fujian Chuanzheng Communications College","ror":"https://ror.org/02k44p231","country_code":null,"type":"education","lineage":["https://openalex.org/I4400600914"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianxing Zhang","raw_affiliation_strings":["College of Information and Intelligent Transportation, Fujian Chuanzheng Communications College, Fuzhou, China"],"raw_orcid":"https://orcid.org/0009-0000-7071-5659","affiliations":[{"raw_affiliation_string":"College of Information and Intelligent Transportation, Fujian Chuanzheng Communications College, Fuzhou, China","institution_ids":["https://openalex.org/I4400600914"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yingping Chen","orcid":"https://orcid.org/0009-0000-7386-3702"},"institutions":[{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]},{"id":"https://openalex.org/I98834328","display_name":"Wuyi University","ror":"https://ror.org/059djzq42","country_code":"CN","type":"education","lineage":["https://openalex.org/I98834328"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingping Chen","raw_affiliation_strings":["College of Civil Engineering and Architecture, Wuyi University, Wuyishan, China"],"raw_orcid":"https://orcid.org/0009-0000-7386-3702","affiliations":[{"raw_affiliation_string":"College of Civil Engineering and Architecture, Wuyi University, Wuyishan, China","institution_ids":["https://openalex.org/I98834328","https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101346509","display_name":"Dehua Wu","orcid":"https://orcid.org/0009-0002-3561-0303"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dehua Wu","raw_affiliation_strings":["College of Civil Engineering, Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-3561-0303","affiliations":[{"raw_affiliation_string":"College of Civil Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":null,"display_name":"Kewei Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4400600914","display_name":"Fujian Chuanzheng Communications College","ror":"https://ror.org/02k44p231","country_code":null,"type":"education","lineage":["https://openalex.org/I4400600914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kewei Zhu","raw_affiliation_strings":["College of Information and Intelligent Transportation, Fujian Chuanzheng Communications College, Fuzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Intelligent Transportation, Fujian Chuanzheng Communications College, Fuzhou, China","institution_ids":["https://openalex.org/I4400600914"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4400600914"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34719292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"208067","last_page":"208077"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9817000031471252,"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":0.9817000031471252,"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":0.00419999985024333,"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":0.002300000051036477,"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/graph","display_name":"Graph","score":0.574999988079071},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5690000057220459},{"id":"https://openalex.org/keywords/control-flow-graph","display_name":"Control flow graph","score":0.42890000343322754},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.42829999327659607},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.37209999561309814},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3637000024318695},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.36340001225471497},{"id":"https://openalex.org/keywords/graph-rewriting","display_name":"Graph rewriting","score":0.36329999566078186}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8095999956130981},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.574999988079071},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5690000057220459},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44609999656677246},{"id":"https://openalex.org/C27458966","wikidata":"https://www.wikidata.org/wiki/Q1187693","display_name":"Control flow graph","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.42829999327659607},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4101000130176544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38760000467300415},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.37209999561309814},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C558772884","wikidata":"https://www.wikidata.org/wiki/Q1508564","display_name":"Graph rewriting","level":3,"score":0.36329999566078186},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26100000739097595},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C192465680","wikidata":"https://www.wikidata.org/wiki/Q1413450","display_name":"Precondition","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2025.3632115","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3632115","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3632115","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3632115","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7038094490","display_name":null,"funder_award_id":"202233","funder_id":"https://openalex.org/F4320327832","funder_display_name":"Shantou Science and Technology Project"}],"funders":[{"id":"https://openalex.org/F4320327832","display_name":"Shantou Science and Technology Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2116341502","https://openalex.org/W2756203131","https://openalex.org/W2802544089","https://openalex.org/W2809133492","https://openalex.org/W2903871660","https://openalex.org/W2965341826","https://openalex.org/W2997848713","https://openalex.org/W3025986213","https://openalex.org/W3035580605","https://openalex.org/W3044263568","https://openalex.org/W3045200674","https://openalex.org/W3090646150","https://openalex.org/W3123191313","https://openalex.org/W3177318507","https://openalex.org/W4317740030","https://openalex.org/W4382239616","https://openalex.org/W4385245566","https://openalex.org/W4388653439","https://openalex.org/W4390543647","https://openalex.org/W4393052006","https://openalex.org/W4393186497","https://openalex.org/W4393352764","https://openalex.org/W4398781884","https://openalex.org/W4402642136","https://openalex.org/W4402930209","https://openalex.org/W4403216603","https://openalex.org/W4408017252","https://openalex.org/W4409023924","https://openalex.org/W4409380285","https://openalex.org/W4410040546","https://openalex.org/W4410376752"],"related_works":[],"abstract_inverted_index":{"Traffic":[0],"flow":[1,97,117,124],"forecasting,":[2],"a":[3,45,100,127,177,190],"critical":[4],"component":[5],"of":[6,26,69,193],"intelligent":[7],"urban":[8],"traffic":[9,96,149],"management,":[10],"faces":[11],"challenges":[12],"such":[13],"as":[14],"complex":[15],"spatio-temporal":[16,39,48],"dependencies":[17],"and":[18,71,123,142,153,182],"diverse":[19],"road":[20],"topologies.":[21],"To":[22],"overcome":[23],"the":[24,66,135],"limitations":[25],"existing":[27],"methods":[28,161],"that":[29,156],"either":[30],"struggle":[31],"with":[32,94,103,166],"graph":[33,73,92],"structure":[34],"modeling":[35,197],"or":[36],"lack":[37],"explicit":[38],"relationship":[40],"representation,":[41],"this":[42],"paper":[43],"proposes":[44],"novel":[46],"graph-aware":[47],"forecasting":[49],"model":[50,58,102,111],"named":[51],"Modulated":[52],"Graph":[53,60],"Token":[54],"Network":[55],"(ModuNet).":[56],"The":[57,173],"utilizes":[59],"Convolutional":[61],"Networks":[62],"(GCNs)":[63],"to":[64,75,90,109,115,118,121,125,138],"extract":[65],"topological":[67],"features":[68],"nodes":[70],"constructs":[72],"tokens":[74,93],"capture":[76,139],"structural":[77],"information.":[78],"A":[79],"modulation":[80],"transformation":[81],"matrix,":[82],"shared":[83],"across":[84,162],"all":[85],"time":[86,195],"steps,":[87],"is":[88,107],"introduced":[89],"integrate":[91],"sequential":[95],"data.":[98],"Subsequently,":[99],"Transformer":[101],"an":[104],"encoder-decoder":[105],"architecture":[106],"employed":[108],"explicitly":[110],"four":[112],"core":[113],"relationships\u2014node":[114],"node,":[116],"flow,":[119,122],"node":[120],"node\u2014within":[126],"unified":[128],"attention":[129],"mechanism.":[130],"This":[131],"design":[132],"significantly":[133],"enhances":[134],"model's":[136],"capacity":[137],"both":[140],"short-term":[141],"long-term":[143,171],"dependencies.":[144],"Experiments":[145],"on":[146],"three":[147],"public":[148],"datasets,":[150],"PeMSD7,":[151],"PeMSD8":[152],"METR-LA,":[154],"show":[155],"ModuNet":[157],"consistently":[158],"outperforms":[159],"mainstream":[160],"various":[163],"prediction":[164],"horizons,":[165],"particularly":[167],"strong":[168,183],"performance":[169],"in":[170],"forecasting.":[172],"proposed":[174],"method":[175],"offers":[176],"clear":[178],"structure,":[179],"controllable":[180],"parameters,":[181],"generalizability,":[184],"making":[185],"it":[186],"well":[187],"suited":[188],"for":[189],"wide":[191],"range":[192],"graph-based":[194],"series":[196],"tasks.":[198]},"counts_by_year":[],"updated_date":"2025-12-16T23:43:54.943958","created_date":"2025-11-12T00:00:00"}