{"id":"https://openalex.org/W4214692098","doi":"https://doi.org/10.1080/13658816.2022.2032081","title":"A multi-view bidirectional spatiotemporal graph network for urban traffic flow imputation","display_name":"A multi-view bidirectional spatiotemporal graph network for urban traffic flow imputation","publication_year":2022,"publication_date":"2022-02-28","ids":{"openalex":"https://openalex.org/W4214692098","doi":"https://doi.org/10.1080/13658816.2022.2032081"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2022.2032081","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2022.2032081","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"],"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/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/A5100378774","display_name":"Tong Zhang","orcid":"https://orcid.org/0000-0002-0683-4669"},"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":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"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036092538","display_name":"Yueming Zheng","orcid":"https://orcid.org/0000-0003-0664-8409"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueming Zheng","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","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"]}]}],"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":7.2334,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":{"value":0.981893,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"36","issue":"6","first_page":"1231","last_page":"1257"},"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":0.9950000047683716,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.8047884106636047},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.6678484678268433},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6309956312179565},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6054054498672485},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5342879295349121},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.5114978551864624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1936415731906891},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.17709994316101074},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1752503514289856}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8047884106636047},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.6678484678268433},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6309956312179565},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6054054498672485},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5342879295349121},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.5114978551864624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1936415731906891},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.17709994316101074},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1752503514289856},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/13658816.2022.2032081","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2022.2032081","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8500000238418579}],"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":59,"referenced_works":["https://openalex.org/W1789808336","https://openalex.org/W1968507337","https://openalex.org/W1973749534","https://openalex.org/W1973943669","https://openalex.org/W1979646154","https://openalex.org/W2036317923","https://openalex.org/W2038206846","https://openalex.org/W2074038916","https://openalex.org/W2085103107","https://openalex.org/W2089625383","https://openalex.org/W2098148222","https://openalex.org/W2099596680","https://openalex.org/W2105418135","https://openalex.org/W2190353863","https://openalex.org/W2222783860","https://openalex.org/W2277710627","https://openalex.org/W2468907370","https://openalex.org/W2535805784","https://openalex.org/W2541565311","https://openalex.org/W2552480641","https://openalex.org/W2564747559","https://openalex.org/W2611552022","https://openalex.org/W2684846153","https://openalex.org/W2756203131","https://openalex.org/W2779684064","https://openalex.org/W2789788750","https://openalex.org/W2805089611","https://openalex.org/W2888834993","https://openalex.org/W2891406408","https://openalex.org/W2901504064","https://openalex.org/W2902048196","https://openalex.org/W2904832339","https://openalex.org/W2907492528","https://openalex.org/W2945769134","https://openalex.org/W2948010559","https://openalex.org/W2993438196","https://openalex.org/W3001909761","https://openalex.org/W3004008526","https://openalex.org/W3004584189","https://openalex.org/W3006452720","https://openalex.org/W3012295089","https://openalex.org/W3034277777","https://openalex.org/W3034749137","https://openalex.org/W3034951560","https://openalex.org/W3037624214","https://openalex.org/W3089251088","https://openalex.org/W3091014027","https://openalex.org/W3102963309","https://openalex.org/W3103720336","https://openalex.org/W3120345119","https://openalex.org/W3152838014","https://openalex.org/W3203580723","https://openalex.org/W4245245123","https://openalex.org/W4362597614","https://openalex.org/W4362597616","https://openalex.org/W6600050674","https://openalex.org/W6600175266","https://openalex.org/W6600565697","https://openalex.org/W7045313712"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W2903115227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516"],"abstract_inverted_index":{"Accurate":[0],"estimation":[1],"of":[2,8,35,45,142],"missing":[3,23,36,46,70,170,180],"traffic":[4,24,37,47,66,82,153],"data":[5,19,67],"is":[6,136],"one":[7],"the":[9,43,114,120,129,140,143],"essential":[10],"components":[11],"in":[12,156],"intelligent":[13],"transportation":[14],"systems":[15],"(ITS).":[16],"The":[17,146],"non-Euclidean":[18],"structure":[20],"and":[21,96,176,179],"complex":[22,69],"flow":[25],"patterns":[26],"make":[27],"it":[28],"challenging":[29],"to":[30,63,79,112,138],"capture":[31],"nonlinear":[32],"spatiotemporal":[33,58,74,103],"correlations":[34],"flow,":[38],"which":[39],"are":[40,77,106],"critical":[41],"for":[42],"imputation":[44,116],"data.":[48],"In":[49],"this":[50],"study,":[51],"we":[52],"propose":[53],"a":[54,109,123],"novel":[55,124],"multi-view":[56],"bidirectional":[57,102],"graph":[59,75,104],"network":[60],"called":[61],"Multi-BiSTGN":[62,121,144,163],"impute":[64],"urban":[65],"with":[68],"patterns.":[71],"First,":[72],"three":[73,101,132],"sequences":[76],"constructed":[78],"comprehensively":[80],"describe":[81],"conditions":[83],"from":[84],"different":[85,169],"temporal":[86,90,133],"correlation":[87,134],"views,":[88],"i.e.":[89],"closeness":[91],"view,":[92,95],"daily":[93],"periodicity":[94,98],"weekly":[97],"view.":[99],"Then,":[100],"networks":[105],"fused":[107],"by":[108],"parametric-matrix-based":[110],"method":[111],"obtain":[113],"final":[115],"results.":[117],"To":[118],"train":[119],"model,":[122],"loss":[125],"function":[126],"that":[127,162],"considers":[128],"interactions":[130],"between":[131],"views":[135],"designed":[137],"optimize":[139],"parameters":[141],"model.":[145],"proposed":[147],"model":[148],"was":[149],"validated":[150],"on":[151],"real-world":[152],"datasets":[154],"collected":[155],"Wuhan,":[157],"China.":[158],"Experimental":[159],"results":[160],"showed":[161],"outperformed":[164],"ten":[165],"existing":[166],"baselines":[167],"under":[168],"types":[171],"(random":[172],"missing,":[173,175],"block":[174],"mixed":[177],"missing)":[178],"rates.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":11}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
