{"id":"https://openalex.org/W7225618095","doi":"https://doi.org/10.1038/s41598-026-80267-w","title":"Dynamic spatiotemporal graph network with a temporal masked transformer for traffic flow forecasting","display_name":"Dynamic spatiotemporal graph network with a temporal masked transformer for traffic flow forecasting","publication_year":2026,"publication_date":"2026-11-09","ids":{"openalex":"https://openalex.org/W7225618095","doi":"https://doi.org/10.1038/s41598-026-80267-w"},"language":"en","primary_location":{"id":"doi:10.1038/s41598-026-80267-w","doi":"https://doi.org/10.1038/s41598-026-80267-w","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-80267-w","pdf_url":"https://www.nature.com/articles/s41598-026-80267-w_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.nature.com/articles/s41598-026-80267-w_reference.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5146857994","display_name":"Zuojun Wu","orcid":"https://orcid.org/0009-0005-0556-9217","observed_orcids":["https://orcid.org/0009-0005-0556-9217"]},"institutions":[{"id":"https://openalex.org/I4405278512","display_name":"Shandong Institute of Petroleum and Chemical Technology","ror":"https://ror.org/00581xj59","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405278512"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zuojun Wu","raw_affiliation_strings":["College of Intelligent Manufacturing and Control Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying, 257000, China"],"raw_orcid":"https://orcid.org/0009-0005-0556-9217","affiliations":[{"raw_affiliation_string":"College of Intelligent Manufacturing and Control Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying, 257000, China","institution_ids":["https://openalex.org/I4405278512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412703","display_name":"Xiaojun Liu","orcid":"https://orcid.org/0000-0002-2874-1500","observed_orcids":["https://orcid.org/0000-0002-2874-1500"]},"institutions":[{"id":"https://openalex.org/I4405278512","display_name":"Shandong Institute of Petroleum and Chemical Technology","ror":"https://ror.org/00581xj59","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405278512"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Liu","raw_affiliation_strings":["College of Intelligent Manufacturing and Control Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying, 257000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligent Manufacturing and Control Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying, 257000, China","institution_ids":["https://openalex.org/I4405278512"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126301528","display_name":"Xiaoling Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405278512","display_name":"Shandong Institute of Petroleum and Chemical Technology","ror":"https://ror.org/00581xj59","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405278512"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoling Zhang","raw_affiliation_strings":["College of Intelligent Manufacturing and Control Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying, 257000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligent Manufacturing and Control Engineering, Shandong Institute of Petroleum and Chemical Technology, Dongying, 257000, China","institution_ids":["https://openalex.org/I4405278512"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5146857994"],"corresponding_institution_ids":["https://openalex.org/I4405278512"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":0.0,"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"}},{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/traffic-flow-prediction","display_name":"traffic flow prediction","score":1.0},{"id":"https://openalex.org/keywords/dynamic-graph-construction","display_name":"dynamic graph construction","score":0.8349999785423279},{"id":"https://openalex.org/keywords/temporal-dependencies","display_name":"temporal dependencies","score":0.5609999895095825},{"id":"https://openalex.org/keywords/pems-datasets","display_name":"PeMS dataset","score":0.49399998784065247}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7803999781608582},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6031000018119812},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.48420000076293945},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4578000009059906},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.450300008058548},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39809998869895935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3939000070095062},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.358599990606308},{"id":"https://openalex.org/C2993660032","wikidata":"https://www.wikidata.org/wiki/Q746984","display_name":"Traffic speed","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28380000591278076},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s41598-026-80267-w","doi":"https://doi.org/10.1038/s41598-026-80267-w","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-80267-w","pdf_url":"https://www.nature.com/articles/s41598-026-80267-w_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s41598-026-80267-w","doi":"https://doi.org/10.1038/s41598-026-80267-w","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-80267-w","pdf_url":"https://www.nature.com/articles/s41598-026-80267-w_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.761900007724762},{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.7207000255584717}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225618095.pdf","grobid_xml":"https://content.openalex.org/works/W7225618095.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2085592822","https://openalex.org/W2120121938","https://openalex.org/W2145331597","https://openalex.org/W2158787690","https://openalex.org/W2269895670","https://openalex.org/W2618170429","https://openalex.org/W2950556849","https://openalex.org/W3088611441","https://openalex.org/W4291910343","https://openalex.org/W4402332810","https://openalex.org/W4405821279","https://openalex.org/W4406059659","https://openalex.org/W4406367746","https://openalex.org/W4407867039","https://openalex.org/W4411550769","https://openalex.org/W4412629916","https://openalex.org/W4415616382","https://openalex.org/W7128794630","https://openalex.org/W7152616987","https://openalex.org/W7162135864","https://openalex.org/W7164743991","https://openalex.org/W7167607798","https://openalex.org/W7167624793","https://openalex.org/W7172532608","https://openalex.org/W7203725726"],"related_works":["https://openalex.org/W4417178865","https://openalex.org/W4396978893","https://openalex.org/W7213965678","https://openalex.org/W4308444436","https://openalex.org/W4404115430","https://openalex.org/W4395956592","https://openalex.org/W4403242250","https://openalex.org/W7169841758","https://openalex.org/W4361271978","https://openalex.org/W4410475097"],"abstract_inverted_index":{"Accurate":[0],"traffic":[1,17,42,218],"flow":[2,219],"forecasting":[3,132,139],"requires":[4],"a":[5,50,56,94,113,118],"model":[6],"to":[7,37,70,106],"capture":[8,107],"time-varying":[9],"spatial":[10,88],"correlations,":[11],"nonlocal":[12],"temporal":[13,31,90,95,109,158,195,200,213],"dependencies,":[14],"and":[15,78,89,134,144,155,174,198],"recurring":[16],"patterns":[18],"simultaneously.":[19],"Existing":[20],"spatiotemporal":[21],"models":[22],"often":[23],"rely":[24],"on":[25,161],"fixed":[26],"relational":[27],"graphs":[28],"or":[29],"local":[30],"operators,":[32],"which":[33],"limits":[34],"their":[35],"ability":[36],"represent":[38],"evolving":[39],"dependencies":[40],"in":[41,141],"networks.":[43],"To":[44],"address":[45],"these":[46],"limitations,":[47],"we":[48],"propose":[49],"Dynamic":[51],"Spatiotemporal":[52],"Graph":[53],"Network":[54],"with":[55,66,123,211],"Temporal":[57,114],"Masked":[58,115],"Transformer":[59,116,121],"(DSGN-TMT).":[60],"DSGN-TMT":[61,168],"combines":[62],"layer-specific":[63,188],"independent":[64],"blocks":[65,69],"cross-layer":[67,190],"information-sharing":[68],"learn":[71],"complementary":[72,185],"representations":[73],"along":[74],"the":[75,131,146,149,170,184],"spatial,":[76],"temporal,":[77],"feature":[79],"dimensions.":[80],"A":[81],"time-aware":[82],"dynamic":[83,192,208],"graph":[84,96,104,193,196,209],"constructor":[85],"generates":[86],"periodicity-conditioned":[87],"adjacency":[91],"structures,":[92],"while":[93],"convolution":[97],"module":[98],"treats":[99],"historical":[100,151],"time":[101],"slots":[102],"as":[103],"nodes":[105],"flexible":[108],"interactions.":[110],"In":[111],"addition,":[112],"(TMT),":[117],"full-history":[119],"contextual":[120,199,212],"encoder":[122],"an":[124],"optional":[125],"masked-subsequence":[126],"design,":[127],"is":[128,215],"integrated":[129],"into":[130],"network":[133],"trained":[135],"end-to-end":[136],"using":[137],"only":[138],"loss;":[140],"both":[142],"training":[143],"inference,":[145],"TMT":[147],"processes":[148],"complete":[150],"sequence":[152],"without":[153],"masking":[154],"produces":[156],"context-aware":[157],"representations.":[159],"Experiments":[160],"four":[162],"PeMS":[163],"benchmark":[164],"datasets":[165],"show":[166],"that":[167,205],"achieves":[169],"lowest":[171],"MAE,":[172],"RMSE,":[173],"MAPE":[175],"among":[176],"23":[177],"comparison":[178],"methods.":[179],"Ablation":[180],"results":[181,203],"further":[182],"demonstrate":[183],"contributions":[186],"of":[187],"learning,":[189],"sharing,":[191],"construction,":[194],"convolution,":[197],"encoding.":[201],"These":[202],"indicate":[204],"explicitly":[206],"coordinating":[207],"learning":[210],"representation":[214],"effective":[216],"for":[217],"forecasting.":[220]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}
