{"id":"https://openalex.org/W4312852945","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892616","title":"Capturing Local and Global Spatial-Temporal Correlations of Spatial-Temporal Graph Data for Traffic Flow Prediction","display_name":"Capturing Local and Global Spatial-Temporal Correlations of Spatial-Temporal Graph Data for Traffic Flow Prediction","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312852945","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892616"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892616","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Capturing_Local_and_Global_Spatial-Temporal_Correlations_of_Spatial-Temporal_Graph_Data_for_Traffic_Flow_Prediction/21861909","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077156405","display_name":"Shuqin Cao","orcid":"https://orcid.org/0000-0001-7058-7650"},"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"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuqin Cao","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108047844","display_name":"Libing Wu","orcid":"https://orcid.org/0000-0001-9897-1953"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Libing Wu","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421941","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-6449-8379"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380474","display_name":"Jianxin Li","orcid":"https://orcid.org/0000-0002-9059-330X"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jianxin Li","raw_affiliation_strings":["School of Information Technology, Deakin University,Melbourne,Victoria,Australia"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Deakin University,Melbourne,Victoria,Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065647746","display_name":"Dan Wu","orcid":"https://orcid.org/0000-0002-2722-8676"},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Dan Wu","raw_affiliation_strings":["School of Computer Science, University of Windsor,Windsor,ON,Canada,N9B 3P4"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Windsor,Windsor,ON,Canada,N9B 3P4","institution_ids":["https://openalex.org/I74413500"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5077156405"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":2.0145,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88658537,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"abs 1911 13181","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":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":0.9884999990463257,"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":0.9855999946594238,"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":0.7297269105911255},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6837862133979797},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5865730047225952},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5830009579658508},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.5141735076904297},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48513635993003845},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.48116716742515564},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.44726884365081787},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4328112304210663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4221786856651306},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24825823307037354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1300269365310669},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09344214200973511},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08679154515266418}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7297269105911255},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6837862133979797},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5865730047225952},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5830009579658508},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.5141735076904297},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48513635993003845},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.48116716742515564},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.44726884365081787},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4328112304210663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4221786856651306},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24825823307037354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1300269365310669},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09344214200973511},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08679154515266418},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892616","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:figshare.com:article/21861909","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Capturing_Local_and_Global_Spatial-Temporal_Correlations_of_Spatial-Temporal_Graph_Data_for_Traffic_Flow_Prediction/21861909","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"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/21861909","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Capturing_Local_and_Global_Spatial-Temporal_Correlations_of_Spatial-Temporal_Graph_Data_for_Traffic_Flow_Prediction/21861909","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":[],"awards":[{"id":"https://openalex.org/G575899936","display_name":null,"funder_award_id":"2021YFB3101104","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8024709401","display_name":null,"funder_award_id":"U20A20177","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W63326460","https://openalex.org/W1970269368","https://openalex.org/W1973943669","https://openalex.org/W1982978808","https://openalex.org/W1990816055","https://openalex.org/W2004353783","https://openalex.org/W2027287130","https://openalex.org/W2133564696","https://openalex.org/W2145039203","https://openalex.org/W2154531209","https://openalex.org/W2156206597","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2572939427","https://openalex.org/W2592311268","https://openalex.org/W2624190409","https://openalex.org/W2751760169","https://openalex.org/W2756203131","https://openalex.org/W2788134583","https://openalex.org/W2901504064","https://openalex.org/W2950817888","https://openalex.org/W2954731415","https://openalex.org/W2962790412","https://openalex.org/W2963358464","https://openalex.org/W2965341826","https://openalex.org/W2989847038","https://openalex.org/W2997848713","https://openalex.org/W2998559444","https://openalex.org/W2999301586","https://openalex.org/W3024644820","https://openalex.org/W3034749137","https://openalex.org/W3038981236","https://openalex.org/W3039941973","https://openalex.org/W3045642713","https://openalex.org/W3080253043","https://openalex.org/W3093761440","https://openalex.org/W3094588037","https://openalex.org/W3103427490","https://openalex.org/W3103720336","https://openalex.org/W3103796199","https://openalex.org/W3126367810","https://openalex.org/W3136849308","https://openalex.org/W3153673236","https://openalex.org/W3158304688","https://openalex.org/W3176075655","https://openalex.org/W3198941940","https://openalex.org/W3206604724","https://openalex.org/W4220941681","https://openalex.org/W4230512065","https://openalex.org/W6600828923","https://openalex.org/W6679434410","https://openalex.org/W6743966852","https://openalex.org/W6746015598","https://openalex.org/W6764679822","https://openalex.org/W6769934737","https://openalex.org/W6780221082","https://openalex.org/W6791513162","https://openalex.org/W6794581564","https://openalex.org/W6810351925"],"related_works":["https://openalex.org/W3148227991","https://openalex.org/W1486593826","https://openalex.org/W2771174107","https://openalex.org/W1536965844","https://openalex.org/W3003272824","https://openalex.org/W2344941099","https://openalex.org/W4322212724","https://openalex.org/W2106788855","https://openalex.org/W3081561710","https://openalex.org/W2477413883"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,64],"prediction":[2],"is":[3],"a":[4,55,88],"challenging":[5],"task":[6],"due":[7],"to":[8,20,48,78,95],"complex":[9],"spatial-temporal":[10],"correlations.":[11,23,33,84],"Most":[12],"existing":[13],"methods":[14],"leverage":[15],"graph":[16,56],"convolutional":[17,57],"network":[18,60],"(GCN)":[19],"capture":[21],"spatial":[22,32,93,100],"However,":[24],"GCN":[25,35],"has":[26],"limited":[27],"ability":[28],"in":[29,43],"mining":[30],"global":[31,82,99],"Multi-layer":[34],"for":[36,62],"aggregating":[37],"multi-order":[38],"neighbor":[39],"information":[40],"will":[41],"result":[42],"high-degree":[44],"nodes":[45],"being":[46],"prone":[47],"over-smoothing.":[49],"To":[50],"this":[51],"end,":[52],"we":[53,67,86],"develop":[54],"recurrent":[58],"attention":[59,94],"(GCRAN)":[61],"traffic":[63,108],"prediction.":[65],"Specifically,":[66],"take":[68],"the":[69],"advantage":[70],"of":[71],"Gated":[72],"Recurrent":[73],"Units":[74],"(GRU)":[75],"and":[76,81,98],"Attention":[77],"explore":[79],"local":[80,90,97],"temporal":[83],"Moreover,":[85],"design":[87],"novel":[89],"context":[91],"aware":[92],"extract":[96],"correlations":[101],"simultaneously.":[102],"Experiments":[103],"on":[104],"two":[105],"public":[106],"real-world":[107],"datasets":[109],"demonstrate":[110],"that":[111],"GCRAN":[112],"outperform":[113],"state-of-the-art":[114],"baselines.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
