{"id":"https://openalex.org/W7125955699","doi":"https://doi.org/10.1109/smc58881.2025.11342712","title":"FE-HGAT: Frequency-Enhanced Hybrid Graph Attention Network For Traffic Prediction","display_name":"FE-HGAT: Frequency-Enhanced Hybrid Graph Attention Network For Traffic Prediction","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125955699","doi":"https://doi.org/10.1109/smc58881.2025.11342712"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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":null,"display_name":"Yao Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Ren","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113391904","display_name":"Wujiang Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wujiang Zhu","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032662894","display_name":"Shiyong Lan","orcid":"https://orcid.org/0000-0002-7109-9170"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyong Lan","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107790517","display_name":"Xinyuan Zhou","orcid":"https://orcid.org/0000-0001-7006-9132"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyuan Zhou","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124077982","display_name":"Hongyu Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Yang","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109785383","display_name":"Zhiang Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiang Hou","raw_affiliation_strings":["Sichuan University,National Key Laboratory of Fundamental Science on Synthetic Vision,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,National Key Laboratory of Fundamental Science on Synthetic Vision,Chengdu,China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5173","last_page":"5178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9894999861717224,"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":0.9894999861717224,"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":0.0034000000450760126,"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":0.0007999999797903001,"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":0.5925999879837036},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4934000074863434},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4555000066757202},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.43070000410079956},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.3767000138759613},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.3765000104904175},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.37119999527931213},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.34279999136924744}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7657999992370605},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5925999879837036},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5435000061988831},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4934000074863434},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.43070000410079956},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.3767000138759613},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.31450000405311584},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C49777392","wikidata":"https://www.wikidata.org/wiki/Q5535495","display_name":"Geometric networks","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C27458966","wikidata":"https://www.wikidata.org/wiki/Q1187693","display_name":"Control flow graph","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C137753397","wikidata":"https://www.wikidata.org/wiki/Q2434424","display_name":"Network science","level":3,"score":0.25870001316070557},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.25699999928474426},{"id":"https://openalex.org/C2993660032","wikidata":"https://www.wikidata.org/wiki/Q746984","display_name":"Traffic speed","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.824323832988739,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1991410369","https://openalex.org/W2069929199","https://openalex.org/W2150884987","https://openalex.org/W2528639018","https://openalex.org/W2756203131","https://openalex.org/W2903871660","https://openalex.org/W2996847713","https://openalex.org/W3045202147","https://openalex.org/W3170140111","https://openalex.org/W3193812480","https://openalex.org/W4302275239","https://openalex.org/W4385270240","https://openalex.org/W4387846860","https://openalex.org/W4390610528","https://openalex.org/W4391308133","https://openalex.org/W4393156599","https://openalex.org/W4402666101","https://openalex.org/W4406615145"],"related_works":[],"abstract_inverted_index":{"Traffic":[0],"flow":[1,68],"prediction":[2],"is":[3,164],"crucial":[4],"for":[5,66],"urban":[6],"traffic":[7,67,98,160],"management":[8],"and":[9,41,49,120,127,138],"planning.":[10],"However,":[11],"although":[12],"existing":[13,34,148],"research":[14],"has":[15],"achieved":[16],"promising":[17],"results,":[18],"most":[19],"methods":[20],"primarily":[21],"focus":[22],"on":[23,151],"time-domain":[24],"processing,":[25],"with":[26],"insufficient":[27],"exploration":[28],"of":[29],"frequency-domain":[30,89],"signal":[31],"characteristics.":[32],"Moreover,":[33],"approaches":[35],"often":[36],"fail":[37],"to":[38,86,101,116,134],"effectively":[39],"distinguish":[40,117],"simultaneously":[42],"model":[43,135],"the":[44,77,94],"spatial":[45,103],"dependencies":[46,96,104,137],"between":[47,105,118],"nearby":[48,119],"distant":[50,121],"nodes.":[51],"To":[52],"address":[53],"these":[54],"issues,":[55],"this":[56],"paper":[57],"proposes":[58],"a":[59,73,112,128],"Frequency-Enhanced":[60],"Hybrid":[61],"Graph":[62],"Attention":[63],"Network":[64],"(FE-HGAT)":[65],"prediction.":[69],"Our":[70],"approach":[71],"employs":[72],"dynamic":[74,113],"filter":[75],"in":[76,97,159],"temporal":[78,95],"dimension,":[79],"which":[80],"utilizes":[81],"Fast":[82],"Fourier":[83],"Transform":[84],"(FFT)":[85],"enhance":[87],"key":[88],"features,":[90],"thereby":[91],"better":[92],"characterizing":[93],"data.":[99],"Besides,":[100],"capture":[102],"nodes":[106],"at":[107,166],"varying":[108],"distances,":[109],"we":[110],"design":[111],"threshold":[114],"module":[115],"nodes,":[122],"employing":[123],"external":[124],"attention":[125,131],"(EA)":[126],"mixture-of-experts-enhanced":[129],"graph":[130],"network":[132],"(MOE-GAT)":[133],"local":[136],"long-distance":[139],"semantic":[140],"similarities,":[141],"respectively.":[142],"Experiments":[143],"demonstrate":[144],"that":[145],"FE-HGAT":[146],"outperforms":[147],"baseline":[149],"models":[150],"several":[152],"public":[153],"transportation":[154],"datasets,":[155],"validating":[156],"its":[157],"effectiveness":[158],"forecasting.":[161],"The":[162],"code":[163],"available":[165],"https://github.com/ry123scuer/FE-HGAT.":[167]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-01-29T00:00:00"}