{"id":"https://openalex.org/W3215209860","doi":"https://doi.org/10.1080/09540091.2021.2006607","title":"Graph learning-based spatial-temporal graph convolutional neural networks for traffic forecasting","display_name":"Graph learning-based spatial-temporal graph convolutional neural networks for traffic forecasting","publication_year":2021,"publication_date":"2021-11-30","ids":{"openalex":"https://openalex.org/W3215209860","doi":"https://doi.org/10.1080/09540091.2021.2006607","mag":"3215209860"},"language":"en","primary_location":{"id":"doi:10.1080/09540091.2021.2006607","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2021.2006607","pdf_url":null,"source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":false,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1080/09540091.2021.2006607","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100685461","display_name":"Na Hu","orcid":"https://orcid.org/0000-0001-6362-0969"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Na Hu","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, People's Republic of China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101594820","display_name":"Dafang Zhang","orcid":"https://orcid.org/0000-0003-0765-6857"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dafang Zhang","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, People's Republic of China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062119492","display_name":"Kun Xie","orcid":"https://orcid.org/0000-0002-2163-2723"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Xie","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, People's Republic of China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078519973","display_name":"Wei Liang","orcid":"https://orcid.org/0000-0002-5074-1363"},"institutions":[{"id":"https://openalex.org/I121296143","display_name":"Hunan University of Science and Technology","ror":"https://ror.org/02m9vrb24","country_code":"CN","type":"education","lineage":["https://openalex.org/I121296143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liang","raw_affiliation_strings":["School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, People's Republic of China","institution_ids":["https://openalex.org/I121296143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109506742","display_name":"Meng-Yen Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I177918364","display_name":"Providence University","ror":"https://ror.org/03fcpsq87","country_code":"TW","type":"education","lineage":["https://openalex.org/I177918364"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Meng-Yen Hsieh","raw_affiliation_strings":["The Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan","institution_ids":["https://openalex.org/I177918364"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100685461","https://openalex.org/A5109506742"],"corresponding_institution_ids":["https://openalex.org/I16609230","https://openalex.org/I177918364"],"apc_list":{"value":1270,"currency":"USD","value_usd":1270},"apc_paid":{"value":1270,"currency":"USD","value_usd":1270},"fwci":4.1319,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.94256917,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"34","issue":"1","first_page":"429","last_page":"448"},"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":0.9973999857902527,"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":0.9951000213623047,"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/computer-science","display_name":"Computer science","score":0.80402672290802},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6260862350463867},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4846697151660919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4666922688484192},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.45007801055908203},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4379211664199829},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43603286147117615},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42037883400917053},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3370388150215149},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2961353659629822},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18089625239372253}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.80402672290802},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6260862350463867},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4846697151660919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4666922688484192},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.45007801055908203},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4379211664199829},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43603286147117615},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42037883400917053},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3370388150215149},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2961353659629822},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18089625239372253}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/09540091.2021.2006607","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2021.2006607","pdf_url":null,"source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":false,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3436c0bb53c945b7b535fb213ac7f0a4","is_oa":false,"landing_page_url":"https://doaj.org/article/3436c0bb53c945b7b535fb213ac7f0a4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Connection Science, Vol 34, Iss 1, Pp 429-448 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/09540091.2021.2006607","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2021.2006607","pdf_url":null,"source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":false,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8704805951","display_name":null,"funder_award_id":"61976087","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W562725408","https://openalex.org/W1973943669","https://openalex.org/W2025391890","https://openalex.org/W2036785686","https://openalex.org/W2038622450","https://openalex.org/W2064675550","https://openalex.org/W2073640212","https://openalex.org/W2073795924","https://openalex.org/W2125817951","https://openalex.org/W2132711183","https://openalex.org/W2133564696","https://openalex.org/W2145039203","https://openalex.org/W2157331557","https://openalex.org/W2165991108","https://openalex.org/W2171234954","https://openalex.org/W2468907370","https://openalex.org/W2519887557","https://openalex.org/W2528639018","https://openalex.org/W2567070169","https://openalex.org/W2567289819","https://openalex.org/W2579495707","https://openalex.org/W2624431344","https://openalex.org/W2626778328","https://openalex.org/W2756203131","https://openalex.org/W2768008502","https://openalex.org/W2782791108","https://openalex.org/W2788134583","https://openalex.org/W2807894308","https://openalex.org/W2809366716","https://openalex.org/W2903871660","https://openalex.org/W2904449562","https://openalex.org/W2904832339","https://openalex.org/W2922146383","https://openalex.org/W2940616741","https://openalex.org/W2948729509","https://openalex.org/W2949382160","https://openalex.org/W2952740813","https://openalex.org/W2963358464","https://openalex.org/W2963970792","https://openalex.org/W2963984147","https://openalex.org/W2965262829","https://openalex.org/W2965341826","https://openalex.org/W2996451395","https://openalex.org/W3001437801","https://openalex.org/W3029409054","https://openalex.org/W3090083930","https://openalex.org/W3103720336","https://openalex.org/W3152893625","https://openalex.org/W3160843674","https://openalex.org/W3185561982","https://openalex.org/W4236133481","https://openalex.org/W4285718364","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W4231775656","https://openalex.org/W2611989081","https://openalex.org/W4321487865","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W4383602045"],"abstract_inverted_index":{"Traffic":[0],"forecasting":[1,28],"is":[2],"highly":[3],"challenging":[4],"due":[5,29],"to":[6,30,95,122],"its":[7,31],"complex":[8],"spatial":[9,36,44,57,87,99],"and":[10,109],"temporal":[11,125],"dependencies":[12,45,58],"in":[13,34,46,62,101,127],"the":[14,47,56,63,85,97,102,143],"traffic":[15,27,48,81,103,128,137],"network.":[16,104],"Graph":[17],"Convolutional":[18],"Neural":[19],"Network":[20],"(GCN)":[21],"has":[22],"been":[23],"effectively":[24],"used":[25],"for":[26,80],"excellent":[32],"performance":[33,148],"modelling":[35],"dependencies.":[37],"In":[38,66],"most":[39],"existing":[40],"approaches,":[41],"GCN":[42],"models":[43],"network":[49,78],"with":[50,118],"a":[51,71,91,119],"fixed":[52],"adjacency":[53],"matrix.":[54],"However,":[55],"change":[59],"over":[60],"time":[61,108],"actual":[64],"situation.":[65],"this":[67],"paper,":[68],"we":[69,89,112],"propose":[70],"graph":[72,75,92],"learning-based":[73],"spatial-temporal":[74],"convolutional":[76],"neural":[77],"(GLSTGCN)":[79],"forecasting.":[82],"To":[83,105],"capture":[84,123],"dynamic":[86,98],"dependencies,":[88],"design":[90],"learning":[93],"module":[94],"learn":[96],"relationships":[100],"save":[106],"training":[107],"computation":[110],"resources,":[111],"adopt":[113],"dilated":[114],"causal":[115],"convolution":[116],"networks":[117],"gating":[120],"mechanism":[121],"long-term":[124],"correlations":[126],"data.":[129],"We":[130],"conducted":[131],"extensive":[132],"experiments":[133],"using":[134],"two":[135],"real-world":[136],"datasets.":[138],"Experimental":[139],"results":[140],"demonstrate":[141],"that":[142],"proposed":[144],"GLSTGCN":[145],"achieves":[146],"superior":[147],"than":[149],"all":[150],"state-of-art":[151],"baselines.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":12}],"updated_date":"2026-06-17T08:01:34.144755","created_date":"2025-10-10T00:00:00"}
