{"id":"https://openalex.org/W3204133755","doi":"https://doi.org/10.1109/access.2021.3114691","title":"Traffic Message Channel Prediction Based on Graph Convolutional Network","display_name":"Traffic Message Channel Prediction Based on Graph Convolutional Network","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3204133755","doi":"https://doi.org/10.1109/access.2021.3114691","mag":"3204133755"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3114691","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3114691","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09546773.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09546773.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100369006","display_name":"Ning Li","orcid":"https://orcid.org/0000-0002-1696-4889"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ning Li","raw_affiliation_strings":["Mogo Auto Intelligence and Telematics Information Technology Co., Ltd, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Mogo Auto Intelligence and Telematics Information Technology Co., Ltd, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091391011","display_name":"Shuang-cheng Jia","orcid":"https://orcid.org/0000-0003-2984-973X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuangcheng Jia","raw_affiliation_strings":["Mogo Auto Intelligence and Telematics Information Technology Co., Ltd, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Mogo Auto Intelligence and Telematics Information Technology Co., Ltd, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100340679","display_name":"Qian Li","orcid":"https://orcid.org/0000-0002-6050-8397"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian Li","raw_affiliation_strings":["Mogo Auto Intelligence and Telematics Information Technology Co., Ltd, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Mogo Auto Intelligence and Telematics Information Technology Co., Ltd, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100369006"],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6055,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.66687545,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"135423","last_page":"135431"},"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":0.9945999979972839,"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":0.9940999746322632,"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":0.7308353185653687},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5985608696937561},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5861652493476868},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5622832775115967},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5224777460098267},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5210278034210205},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.4384075999259949},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4363248348236084},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.367737352848053},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3242502808570862},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28455638885498047},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1403822898864746},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12889117002487183},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09962457418441772}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7308353185653687},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5985608696937561},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5861652493476868},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5622832775115967},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5224777460098267},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5210278034210205},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.4384075999259949},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4363248348236084},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.367737352848053},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3242502808570862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28455638885498047},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1403822898864746},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12889117002487183},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09962457418441772},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3114691","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3114691","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09546773.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9449a1d44ac84691bfdf2ff063a543b1","is_oa":true,"landing_page_url":"https://doaj.org/article/9449a1d44ac84691bfdf2ff063a543b1","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 135423-135431 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3114691","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3114691","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09546773.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3204133755.pdf","grobid_xml":"https://content.openalex.org/works/W3204133755.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W43001522","https://openalex.org/W142583486","https://openalex.org/W626441390","https://openalex.org/W1982978808","https://openalex.org/W2041567331","https://openalex.org/W2047332899","https://openalex.org/W2087748410","https://openalex.org/W2111991989","https://openalex.org/W2165991108","https://openalex.org/W2171234954","https://openalex.org/W2257979135","https://openalex.org/W2268120789","https://openalex.org/W2276747974","https://openalex.org/W2365467942","https://openalex.org/W2392708022","https://openalex.org/W2528639018","https://openalex.org/W2561568083","https://openalex.org/W2579495707","https://openalex.org/W2613331518","https://openalex.org/W2743316574","https://openalex.org/W2766447205","https://openalex.org/W2897825916","https://openalex.org/W2913277766","https://openalex.org/W2969855422","https://openalex.org/W3027664001","https://openalex.org/W3033535063","https://openalex.org/W3043505188","https://openalex.org/W6619978402","https://openalex.org/W6672552787","https://openalex.org/W6693782912","https://openalex.org/W6728547873","https://openalex.org/W6767279920","https://openalex.org/W7033820688"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2126145365","https://openalex.org/W1988032185","https://openalex.org/W2898021863","https://openalex.org/W3121692546","https://openalex.org/W2521335480","https://openalex.org/W2611370603"],"abstract_inverted_index":{"With":[0],"the":[1,31,37,58,74,86,101,106,157,166,177,185,190,196],"development":[2],"of":[3,14,36,85,136,159,169,180,187],"big":[4],"data,":[5,160],"large-scale":[6],"traffic":[7,27,46,60,65,181],"flow":[8,28,47,61,66],"forecasting":[9],"which":[10,123,132],"is":[11,30,104,111,153,162,173,193],"a":[12,53,69,118,134],"part":[13,35],"smart":[15],"transportation":[16],"has":[17],"become":[18],"an":[19],"increasingly":[20],"important":[21],"research":[22],"direction.":[23],"Accurate":[24],"and":[25,33,44,57,63,94,145],"real-time":[26],"prediction":[29,121],"key":[32],"difficult":[34],"traffic.":[38],"The":[39],"complex":[40,70],"spatial":[41,55,96,102],"topological":[42,107],"structure":[43],"dynamic":[45],"information":[48],"in":[49],"urban":[50,170],"roads":[51],"constitute":[52,68],"changeable":[54],"correlation,":[56],"daily":[59],"cycle":[62,67],"weekly":[64],"time":[71,92,178],"correlation.":[72,97],"For":[73],"current":[75,197],"mainstream":[76,198],"model,":[77,122,131],"there":[78],"are":[79],"two":[80],"main":[81],"limitations:":[82],"1.":[83],"Most":[84],"existing":[87],"models":[88],"only":[89],"focus":[90],"on":[91],"correlation":[93,103,179],"ignore":[95],"2.":[98],"Even":[99],"if":[100],"concerned,":[105],"relationship":[108],"between":[109],"spaces":[110],"not":[112],"fully":[113],"considered.":[114],"This":[115],"paper":[116],"proposes":[117],"new":[119],"traffic-flow":[120],"named":[124],"Principal":[125,137],"Spatio-Temporal":[126],"Graph":[127,141],"Convolution":[128,142],"Network":[129,143],"(PST-GCN)":[130],"uses":[133],"combination":[135],"Component":[138],"Analysis":[139],"(PCA),":[140],"(GCN),":[144],"Long":[146],"Short-Term":[147],"Memory":[148],"model":[149,192],"(LSTM).":[150],"Specifically,":[151],"PCA":[152],"used":[154,163,174],"to":[155,164,175],"reduce":[156],"dimension":[158],"GCN":[161],"learn":[165],"network":[167],"topology":[168],"roads,":[171],"LSTM":[172],"capture":[176],"flow.":[182],"By":[183],"comparing":[184],"results":[186],"different":[188],"models,":[189],"proposed":[191],"better":[194],"than":[195],"models.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-29T08:15:47.926485","created_date":"2025-10-10T00:00:00"}