{"id":"https://openalex.org/W4285272621","doi":"https://doi.org/10.1109/tits.2022.3171451","title":"AARGNN: An Attentive Attributed Recurrent Graph Neural Network for Traffic Flow Prediction Considering Multiple Dynamic Factors","display_name":"AARGNN: An Attentive Attributed Recurrent Graph Neural Network for Traffic Flow Prediction Considering Multiple Dynamic Factors","publication_year":2022,"publication_date":"2022-05-04","ids":{"openalex":"https://openalex.org/W4285272621","doi":"https://doi.org/10.1109/tits.2022.3171451"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3171451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3171451","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/A5100411139","display_name":"Ling Chen","orcid":"https://orcid.org/0000-0003-1934-5992"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ling Chen","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101520496","display_name":"Wei Shao","orcid":"https://orcid.org/0000-0002-3700-8431"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Shao","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068773146","display_name":"Mingqi Lv","orcid":"https://orcid.org/0000-0003-4810-7491"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingqi Lv","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100646104","display_name":"Weiqi Chen","orcid":"https://orcid.org/0009-0007-9246-9402"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqi Chen","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052676996","display_name":"Youdong Zhang","orcid":"https://orcid.org/0009-0000-8351-9091"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youdong Zhang","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101661188","display_name":"Yang Cheng-hu","orcid":"https://orcid.org/0000-0002-1062-383X"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenghu Yang","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100411139"],"corresponding_institution_ids":["https://openalex.org/I168879160"],"apc_list":null,"apc_paid":null,"fwci":6.0462,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.97392943,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"23","issue":"10","first_page":"17201","last_page":"17211"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6954192519187927},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6281169652938843},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5199459791183472},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5158337950706482},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5108579993247986},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4977162182331085},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.495978444814682},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47589075565338135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3489815592765808},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32998228073120117},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.23285022377967834},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16571912169456482},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1619674563407898},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.150013267993927},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13115298748016357},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12087884545326233}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6954192519187927},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6281169652938843},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5199459791183472},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5158337950706482},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5108579993247986},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4977162182331085},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.495978444814682},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47589075565338135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3489815592765808},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32998228073120117},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.23285022377967834},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16571912169456482},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1619674563407898},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.150013267993927},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13115298748016357},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12087884545326233},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3171451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3171451","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":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1317677795","display_name":null,"funder_award_id":"U1936215","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1583088338","display_name":null,"funder_award_id":"2018YFB0505000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1973943669","https://openalex.org/W1991770012","https://openalex.org/W2002644193","https://openalex.org/W2004353783","https://openalex.org/W2012051283","https://openalex.org/W2040297119","https://openalex.org/W2083238230","https://openalex.org/W2090192376","https://openalex.org/W2125817951","https://openalex.org/W2145039203","https://openalex.org/W2150010190","https://openalex.org/W2150263714","https://openalex.org/W2158107760","https://openalex.org/W2171234954","https://openalex.org/W2173492666","https://openalex.org/W2190353863","https://openalex.org/W2343480289","https://openalex.org/W2392708022","https://openalex.org/W2579495707","https://openalex.org/W2606780347","https://openalex.org/W2613331518","https://openalex.org/W2756203131","https://openalex.org/W2782432998","https://openalex.org/W2793820729","https://openalex.org/W2805516822","https://openalex.org/W2901504064","https://openalex.org/W2903871660","https://openalex.org/W2904449562","https://openalex.org/W2904832339","https://openalex.org/W2935726879","https://openalex.org/W2963091558","https://openalex.org/W2972752351","https://openalex.org/W2996451395","https://openalex.org/W2997848713","https://openalex.org/W2998559444","https://openalex.org/W2999301586","https://openalex.org/W3015851013","https://openalex.org/W3026400623","https://openalex.org/W3027664001","https://openalex.org/W3103720336","https://openalex.org/W3126693873","https://openalex.org/W3128987237","https://openalex.org/W3133349961","https://openalex.org/W3133663379","https://openalex.org/W4377555580","https://openalex.org/W6720006811","https://openalex.org/W6746015598","https://openalex.org/W6751796012","https://openalex.org/W6852680047"],"related_works":["https://openalex.org/W2149721642","https://openalex.org/W2587362999","https://openalex.org/W432084041","https://openalex.org/W2394010358","https://openalex.org/W2361078351","https://openalex.org/W2986732134","https://openalex.org/W4239349137","https://openalex.org/W1463884142","https://openalex.org/W2963251637","https://openalex.org/W239469043"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,27,35],"prediction":[2,28,36],"is":[3,29],"a":[4,30,81],"fundamental":[5],"part":[6],"of":[7,15,59,149,171],"ITS":[8],"(Intelligent":[9],"Transportation":[10],"System).":[11],"Since":[12],"the":[13,44,57,60,66,130,145,150,157,169,184],"correlations":[14,58,148],"traffic":[16,26,34,61,95,132,151],"data":[17,62,100,152],"are":[18,21,153],"complicated":[19],"and":[20,48,55,113,125,140],"affected":[22],"by":[23,155],"various":[24,142],"factors,":[25],"challenging":[31],"task.":[32],"Existing":[33],"methods":[37],"generally":[38],"take":[39],"limited":[40],"static":[41,111],"factors":[42,91,112,115,143],"(e.g.,":[43,101,116],"distance":[45],"between":[46],"sensors":[47],"road":[49,103,121,123],"network":[50],"topological":[51],"structure)":[52],"into":[53,144],"consideration":[54],"model":[56],"separately":[63],"to":[64,92,128],"predict":[65,93,129],"future":[67],"traffic.":[68],"In":[69,165],"this":[70],"paper,":[71],"we":[72],"propose":[73],"AARGNN":[74,108,135,167],"(Attentive":[75],"Attributed":[76],"Recurrent":[77],"Graph":[78],"Neural":[79],"Network),":[80],"GNN":[82,158],"(graph":[83],"neural":[84],"network)":[85],"based":[86,174],"method":[87,186],"considering":[88],"multiple":[89],"dynamic":[90,114],"short-term":[94,131,163],"flow.":[96,133],"With":[97],"multi-source":[98],"urban":[99],"POI,":[102],"network,":[104],"incident,":[105],"weather,":[106],"etc.),":[107],"considers":[109],"both":[110],"spatial":[117],"distance,":[118,120],"semantic":[119],"characteristic,":[122],"situation,":[124],"global":[126],"context)":[127],"Specifically,":[134],"constructs":[136],"an":[137],"attributed":[138],"graph":[139],"encodes":[141],"attributes.":[146],"The":[147],"modeled":[154],"utilizing":[156],"combined":[159],"with":[160],"LSTM":[161],"(long":[162],"memory).":[164],"addition,":[166],"specifies":[168],"contributions":[170],"each":[172],"factor":[173],"on":[175,179],"attention":[176],"mechanism.":[177],"Experiments":[178],"real-world":[180],"datasets":[181],"show":[182],"that":[183],"proposed":[185],"outperforms":[187],"all":[188],"baseline":[189],"methods.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}