{"id":"https://openalex.org/W4416249855","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228834","title":"MF2former: Multi-Feature Fusion Transformer for Traffic Flow Prediction","display_name":"MF2former: Multi-Feature Fusion Transformer for Traffic Flow Prediction","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416249855","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228834"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5100410563","display_name":"Zihan Zhang","orcid":"https://orcid.org/0009-0004-8852-8156"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zihan Zhang","raw_affiliation_strings":["Tongji University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035948567","display_name":"Shengjie Zhao","orcid":"https://orcid.org/0000-0002-6109-2522"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengjie Zhao","raw_affiliation_strings":["Tongji University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026359194","display_name":"Shilong Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilong Dong","raw_affiliation_strings":["Tongji University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072545226","display_name":"Jiafeng Huang","orcid":"https://orcid.org/0009-0002-0451-1628"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiafeng Huang","raw_affiliation_strings":["Tongji University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103121150","display_name":"Yuhang Wan","orcid":"https://orcid.org/0000-0003-0083-9511"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Wan","raw_affiliation_strings":["Tongji University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078255068","display_name":"Wenzhen Jia","orcid":"https://orcid.org/0000-0002-3730-2622"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhen Jia","raw_affiliation_strings":["Tongji University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029427154","display_name":"Hao Deng","orcid":"https://orcid.org/0000-0003-3240-4352"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Deng","raw_affiliation_strings":["Tongji University,School of Computer Science and Technology"],"affiliations":[{"raw_affiliation_string":"Tongji University,School of Computer Science and Technology","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100410563"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36219158,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9671000242233276,"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":0.9671000242233276,"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":0.0142000000923872,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.0017000000225380063,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5546000003814697},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5195000171661377},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5109999775886536},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.45739999413490295},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.40709999203681946},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4059000015258789},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.3898000121116638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6151000261306763},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5546000003814697},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5109999775886536},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.45739999413490295},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42160001397132874},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4059000015258789},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39890000224113464},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.35339999198913574},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3395000100135803},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.31439998745918274},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28839999437332153},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28349998593330383},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2786000072956085},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2727000117301941},{"id":"https://openalex.org/C16160715","wikidata":"https://www.wikidata.org/wiki/Q1640676","display_name":"Traffic engineering","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C94168897","wikidata":"https://www.wikidata.org/wiki/Q574324","display_name":"Network traffic simulation","level":4,"score":0.2554999887943268},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228834","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2140051110","https://openalex.org/W2142674578","https://openalex.org/W2253276617","https://openalex.org/W2756203131","https://openalex.org/W2965341826","https://openalex.org/W2996847713","https://openalex.org/W2997848713","https://openalex.org/W3039075121","https://openalex.org/W3080253043","https://openalex.org/W3092476034","https://openalex.org/W3174022889","https://openalex.org/W3210546159","https://openalex.org/W4229002088","https://openalex.org/W4306317966","https://openalex.org/W4382239616","https://openalex.org/W4387846860","https://openalex.org/W4390547377","https://openalex.org/W4393159807","https://openalex.org/W4402671864","https://openalex.org/W4410153049"],"related_works":[],"abstract_inverted_index":{"In":[0,40,132],"urban":[1,253],"planning,":[2],"traffic":[3,27,38,65,96,113,117,153,170,220,229,246],"flow":[4,28,66,154,247],"prediction,":[5,248],"a":[6,137,165,241],"core":[7],"component":[8],"of":[9,20,26,95,107,129,152,169,208],"Intelligent":[10],"Transportation":[11],"Systems,":[12],"has":[13,47],"made":[14],"significant":[15],"progress":[16],"with":[17],"the":[18,33,78,83,93,104,116,121,127,141,149,158,174,191,204,209,219],"development":[19],"deep":[21],"learning.":[22],"The":[23],"key":[24],"problem":[25],"prediction":[29],"lies":[30],"in":[31,37,115,218],"capturing":[32],"complex":[34],"spatio-temporal":[35],"correlations":[36],"flow.":[39],"recent":[41],"years,":[42],"more":[43,45],"and":[44,180,202,255],"research":[46],"tended":[48],"to":[49,53,91,123,163,211,235],"apply":[50],"Transformer-based":[51,58,139],"models":[52,59],"solve":[54],"this":[55,133],"problem.":[56],"However,":[57],"have":[60],"two":[61,227],"major":[62],"limitations":[63,151],"for":[64,244,252],"prediction:":[67],"i)":[68],"Most":[69,99],"methods":[70,100],"only":[71],"focus":[72,125,214],"on":[73,126,215],"extracting":[74],"data":[75,171],"features":[76],"within":[77,177],"attention":[79],"head,":[80],"while":[81],"ignoring":[82],"correlation":[84],"between":[85,184],"these":[86,185],"heads,":[87],"making":[88],"it":[89],"difficult":[90],"integrate":[92],"multi-features":[94],"data;":[97],"ii)":[98],"do":[101],"not":[102],"recognize":[103],"unique":[105],"impact":[106],"nodes":[108,198,201,217],"that":[109],"serve":[110],"as":[111],"pivotal":[112,197,216],"hubs":[114],"networks,":[118],"which":[119,195],"cause":[120],"Transformer":[122,144,161,210],"excessively":[124],"influence":[128],"non-pivotal":[130],"nodes.":[131],"study,":[134],"we":[135],"propose":[136],"novel":[138],"model,":[140],"Multi-Feature":[142],"Fusion":[143],"(MF2former),":[145],"aimed":[146],"at":[147],"addressing":[148],"above":[150],"prediction.":[155],"MF2former":[156],"incorporates":[157,190],"Augmented":[159],"Synergistic":[160],"Module":[162],"achieve":[164],"comprehensive":[166],"multi-feature":[167],"fusion":[168,183],"by":[172],"enhancing":[173],"information":[175,182],"capacity":[176],"self-attention":[178],"heads":[179],"performing":[181],"heads.":[186],"Additionally,":[187],"our":[188],"model":[189,223],"Pivotal":[192],"Node":[193],"Module,":[194],"extracts":[196],"from":[199],"all":[200],"masks":[203],"global":[205],"receptive":[206],"field":[207],"enhance":[212],"its":[213],"network.":[221],"Our":[222],"is":[224],"evaluated":[225],"using":[226],"real-world":[228],"datasets,":[230],"demonstrating":[231],"superior":[232],"performance":[233],"compared":[234],"existing":[236],"methods.":[237],"This":[238],"study":[239],"provides":[240],"stable":[242],"framework":[243],"accurate":[245],"offering":[249],"valuable":[250],"insights":[251],"planners":[254],"commuters.":[256]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-14T00:00:00"}