{"id":"https://openalex.org/W4309623216","doi":"https://doi.org/10.1080/13658816.2022.2146120","title":"Urban traffic flow prediction: a dynamic temporal graph network considering missing values","display_name":"Urban traffic flow prediction: a dynamic temporal graph network considering missing values","publication_year":2022,"publication_date":"2022-11-17","ids":{"openalex":"https://openalex.org/W4309623216","doi":"https://doi.org/10.1080/13658816.2022.2146120"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2022.2146120","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2022.2146120","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Urban_traffic_flow_prediction_a_dynamic_temporal_graph_network_considering_missing_values/21571882","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059794331","display_name":"Peixiao Wang","orcid":"https://orcid.org/0000-0002-1209-6340"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peixiao Wang","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456210","display_name":"Yan Zhang","orcid":"https://orcid.org/0000-0002-2059-4171"},"institutions":[{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Zhang","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100706807","display_name":"Tao Hu","orcid":"https://orcid.org/0000-0002-8557-8017"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Hu","raw_affiliation_strings":["Department of Geography, Oklahoma State University, Stillwater, OK, USA"],"affiliations":[{"raw_affiliation_string":"Department of Geography, Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100378774","display_name":"Tong Zhang","orcid":"https://orcid.org/0000-0002-0683-4669"},"institutions":[{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tong Zhang","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100378774"],"corresponding_institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"],"apc_list":null,"apc_paid":null,"fwci":4.8685,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.96062137,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"37","issue":"4","first_page":"885","last_page":"912"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/missing-data","display_name":"Missing data","score":0.5744782090187073},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49177291989326477},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46146586537361145},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.45662721991539},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4206935167312622},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.3732473850250244},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15492820739746094},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1380736231803894}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5744782090187073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49177291989326477},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46146586537361145},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.45662721991539},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4206935167312622},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.3732473850250244},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15492820739746094},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1380736231803894}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/13658816.2022.2146120","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2022.2146120","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/21571882","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Urban_traffic_flow_prediction_a_dynamic_temporal_graph_network_considering_missing_values/21571882","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.6084/m9.figshare.21571882.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.21571882.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/21571882","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Urban_traffic_flow_prediction_a_dynamic_temporal_graph_network_considering_missing_values/21571882","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G8876034744","display_name":null,"funder_award_id":"41871308","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G990590626","display_name":null,"funder_award_id":"2019YFE0106500","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":52,"referenced_works":["https://openalex.org/W2038206846","https://openalex.org/W2190353863","https://openalex.org/W2277710627","https://openalex.org/W2343462218","https://openalex.org/W2528639018","https://openalex.org/W2601251286","https://openalex.org/W2684846153","https://openalex.org/W2756203131","https://openalex.org/W2789788750","https://openalex.org/W2792764867","https://openalex.org/W2805089611","https://openalex.org/W2889230014","https://openalex.org/W2901504064","https://openalex.org/W2902048196","https://openalex.org/W2904449562","https://openalex.org/W2907492528","https://openalex.org/W2916401380","https://openalex.org/W2927836415","https://openalex.org/W2945769134","https://openalex.org/W2964010366","https://openalex.org/W2968900629","https://openalex.org/W2993438196","https://openalex.org/W3005147439","https://openalex.org/W3006452720","https://openalex.org/W3014404134","https://openalex.org/W3016154907","https://openalex.org/W3024861527","https://openalex.org/W3025753202","https://openalex.org/W3034749137","https://openalex.org/W3034951560","https://openalex.org/W3035184251","https://openalex.org/W3037624214","https://openalex.org/W3041552048","https://openalex.org/W3087813748","https://openalex.org/W3089251088","https://openalex.org/W3103720336","https://openalex.org/W3111769493","https://openalex.org/W3148128118","https://openalex.org/W3152838014","https://openalex.org/W3155328257","https://openalex.org/W3162199293","https://openalex.org/W3167202680","https://openalex.org/W3170140111","https://openalex.org/W3184905227","https://openalex.org/W3202811093","https://openalex.org/W3214659126","https://openalex.org/W4210789062","https://openalex.org/W4214692098","https://openalex.org/W4285147743","https://openalex.org/W4294676509","https://openalex.org/W4362597616","https://openalex.org/W6796761347"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2085630472","https://openalex.org/W2308616044","https://openalex.org/W1482410789"],"abstract_inverted_index":{"Accurate":[0],"traffic":[1,25,30,47,65,111,119,165,180],"flow":[2,31,66,112,120],"prediction":[3,32,162,193],"on":[4,93,177],"the":[5,28,71,80,89,94,123,132,141,146,157,169],"urban":[6,24],"road":[7,95],"network":[8,57,104],"is":[9,19,62],"an":[10,178],"indispensable":[11],"function":[12],"of":[13,20],"Intelligent":[14],"Transportation":[15],"Systems":[16],"(ITS),":[17],"which":[18,155],"great":[21],"significance":[22],"for":[23,64,118],"planning.":[26],"However,":[27],"current":[29],"methods":[33],"still":[34],"face":[35],"many":[36],"challenges,":[37],"such":[38],"as":[39],"missing":[40,59,106,115,158,197],"values":[41,60,107,159],"and":[42,161,209,213],"dynamic":[43,53,90,133],"spatial":[44,91,134],"relationships":[45],"in":[46,114,164,183],"flow.":[48],"In":[49],"this":[50],"study,":[51],"a":[52,100,151],"temporal":[54,101],"graph":[55,102],"neural":[56,103],"considering":[58,105],"(D-TGNM)":[61],"proposed":[63,124,170,173],"prediction.":[67,121],"First,":[68],"inspired":[69],"by":[70,130,137],"Bidirectional":[72],"Encoder":[73],"Representations":[74],"from":[75],"Transformers":[76],"(BERT),":[77],"we":[78,98,149],"extend":[79],"classic":[81],"BERT":[82,139],"model,":[83,148],"called":[84],"Traffic":[85,138],"BERT,":[86],"to":[87,109,167],"learn":[88],"associations":[92,135],"structure.":[96],"Second,":[97],"propose":[99],"(TGNM)":[108],"mine":[110],"patterns":[113],"data":[116,198],"scenarios":[117,199],"Finally,":[122],"D-TGNM":[125,147,190],"model":[126,174],"can":[127],"be":[128],"obtained":[129],"integrating":[131],"learned":[136],"into":[140],"TGNM":[142],"model.":[143,171],"To":[144],"train":[145],"design":[150],"novel":[152],"loss":[153],"function,":[154],"considers":[156],"problem":[160,163],"flow,":[166],"optimize":[168],"The":[172],"was":[175],"validated":[176],"actual":[179],"dataset":[181],"collected":[182],"Wuhan,":[184],"China.":[185],"Experimental":[186],"results":[187,194],"showed":[188],"that":[189],"achieved":[191],"good":[192],"under":[195],"four":[196],"(15%":[200],"random":[201,207],"missing,":[202,205,208],"15%":[203],"block":[204,211],"30%":[206,210],"missing),":[212],"outperformed":[214],"ten":[215],"existing":[216],"state-of-the-art":[217],"baselines.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
