{"id":"https://openalex.org/W4417325280","doi":"https://doi.org/10.1007/s40747-025-02146-7","title":"Enhancing traffic flow prediction through multi-view attention mechanism and dilated convolutional networks","display_name":"Enhancing traffic flow prediction through multi-view attention mechanism and dilated convolutional networks","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W4417325280","doi":"https://doi.org/10.1007/s40747-025-02146-7"},"language":"en","primary_location":{"id":"doi:10.1007/s40747-025-02146-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-025-02146-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-025-02146-7.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s40747-025-02146-7.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100318383","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-1733-7956"},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]},{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN","GB"],"is_corresponding":true,"raw_author_name":"Wei Li","raw_affiliation_strings":["Department of Information Communication, Army Arms University of PLA, Beijing, 100072, PR China","National Key Laboratory of Intelligent Parallel Technology, Beijing, 100091, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Communication, Army Arms University of PLA, Beijing, 100072, PR China","institution_ids":["https://openalex.org/I4210163363"]},{"raw_affiliation_string":"National Key Laboratory of Intelligent Parallel Technology, Beijing, 100091, PR China","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100645136","display_name":"Hao Wei","orcid":"https://orcid.org/0009-0005-6053-4455"},"institutions":[{"id":"https://openalex.org/I1329219376","display_name":"National Federation of the Blind","ror":"https://ror.org/059zg8r51","country_code":"US","type":"other","lineage":["https://openalex.org/I1329219376"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Wei","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Blind Signal Processing, Si-chuan, 610041, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Blind Signal Processing, Si-chuan, 610041, PR China","institution_ids":["https://openalex.org/I1329219376"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100737898","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0003-3051-4793"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":["Command and Control Engineering College, Army Engineering University, Nanjing, 210007, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Command and Control Engineering College, Army Engineering University, Nanjing, 210007, PR China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456639","display_name":"Jialin Liu","orcid":"https://orcid.org/0000-0002-1369-4625"},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]},{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Jialin Liu","raw_affiliation_strings":["Department of Information Communication, Army Arms University of PLA, Beijing, 100072, PR China","National Key Laboratory of Intelligent Parallel Technology, Beijing, 100091, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Communication, Army Arms University of PLA, Beijing, 100072, PR China","institution_ids":["https://openalex.org/I4210163363"]},{"raw_affiliation_string":"National Key Laboratory of Intelligent Parallel Technology, Beijing, 100091, PR China","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014299271","display_name":"Dazhi Zhan","orcid":"https://orcid.org/0000-0003-2766-3405"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dazhi Zhan","raw_affiliation_strings":["Command and Control Engineering College, Army Engineering University, Nanjing, 210007, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Command and Control Engineering College, Army Engineering University, Nanjing, 210007, PR China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103038885","display_name":"Xiao Han","orcid":"https://orcid.org/0000-0002-6428-8862"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Han","raw_affiliation_strings":["Command and Control Engineering College, Army Engineering University, Nanjing, 210007, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Command and Control Engineering College, Army Engineering University, Nanjing, 210007, PR China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046355512","display_name":"Wei Tao","orcid":"https://orcid.org/0000-0002-8273-6649"},"institutions":[{"id":"https://openalex.org/I4210162797","display_name":"Hunan Institute of Microbiology","ror":"https://ror.org/054fkw726","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162797"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Tao","raw_affiliation_strings":["Hunan Institute of Advanced Technology, Changsha, 421002, PR China"],"raw_orcid":"https://orcid.org/0000-0002-8273-6649","affiliations":[{"raw_affiliation_string":"Hunan Institute of Advanced Technology, Changsha, 421002, PR China","institution_ids":["https://openalex.org/I4210162797"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100318383"],"corresponding_institution_ids":["https://openalex.org/I4210153682","https://openalex.org/I4210163363"],"apc_list":{"value":1320,"currency":"GBP","value_usd":1619},"apc_paid":{"value":1320,"currency":"GBP","value_usd":1619},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38697673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"1","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":0.9860000014305115,"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":0.9860000014305115,"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/T10524","display_name":"Traffic control and management","score":0.0031999999191612005,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.003100000089034438,"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/variance","display_name":"Variance (accounting)","score":0.48730000853538513},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.48350000381469727},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.47429999709129333},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4571000039577484},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.438400000333786},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4287000000476837},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.37880000472068787},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.3578000068664551},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33079999685287476},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.32510000467300415}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7404000163078308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4912000000476837},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.48350000381469727},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.47429999709129333},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4571000039577484},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.435699999332428},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36899998784065247},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.2660999894142151},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C144745244","wikidata":"https://www.wikidata.org/wiki/Q4927286","display_name":"Blocking (statistics)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C2777489503","wikidata":"https://www.wikidata.org/wiki/Q7698936","display_name":"Temporal scales","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s40747-025-02146-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-025-02146-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-025-02146-7.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:99d92e51fb0348a6a6fbeea3ab7ed283","is_oa":true,"landing_page_url":"https://doaj.org/article/99d92e51fb0348a6a6fbeea3ab7ed283","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complex & Intelligent Systems, Vol 12, Iss 1, Pp 1-17 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s40747-025-02146-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-025-02146-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-025-02146-7.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4694014906","display_name":null,"funder_award_id":"2024M764294","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G4772093540","display_name":null,"funder_award_id":"62576351","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417325280.pdf","grobid_xml":"https://content.openalex.org/works/W4417325280.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2024558842","https://openalex.org/W2064675550","https://openalex.org/W2147800946","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2604862142","https://openalex.org/W2756203131","https://openalex.org/W2766736793","https://openalex.org/W2788134583","https://openalex.org/W2802558403","https://openalex.org/W2805992315","https://openalex.org/W2808011586","https://openalex.org/W2811084102","https://openalex.org/W2921532413","https://openalex.org/W2962790412","https://openalex.org/W2963446712","https://openalex.org/W2975118617","https://openalex.org/W3015553263","https://openalex.org/W3033535063","https://openalex.org/W3034749137","https://openalex.org/W3043505188","https://openalex.org/W3107577028","https://openalex.org/W3123909522","https://openalex.org/W3182298780","https://openalex.org/W3190032105","https://openalex.org/W4210427992","https://openalex.org/W4221058635","https://openalex.org/W4226348734","https://openalex.org/W4249736682","https://openalex.org/W4282002715","https://openalex.org/W4285262037","https://openalex.org/W4297984414","https://openalex.org/W4319335877","https://openalex.org/W4392877658","https://openalex.org/W4394996642","https://openalex.org/W4399728019","https://openalex.org/W4400727150","https://openalex.org/W4403210154","https://openalex.org/W4404295456","https://openalex.org/W4411017343"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Accurate":[1],"traffic":[2,33,71,166],"flow":[3],"forecasting":[4],"serves":[5],"as":[6],"a":[7,86,92,146],"cornerstone":[8],"for":[9],"intelligent":[10],"transportation":[11],"systems,":[12],"enabling":[13],"proactive":[14],"accident":[15],"prevention":[16],"and":[17,49,60,64,112,135,155,182],"metropolitan":[18],"mobility":[19],"optimization.":[20],"However,":[21],"existing":[22],"approaches":[23],"face":[24],"fundamental":[25],"limitations":[26],"in":[27,36,69,171,184],"modeling":[28],"the":[29,40],"spatiotemporal":[30,174],"heterogeneity":[31,124],"of":[32,43,180],"dynamics,":[34],"particularly":[35],"simultaneously":[37],"addressing":[38],"(1)":[39],"decaying":[41,136],"significance":[42],"temporal":[44,67,94,100,110,115,122,133],"dependencies":[45],"across":[46],"input":[47],"sequences":[48],"prediction":[50],"horizons,":[51],"(2)":[52],"multi-scale":[53,156],"spatial":[54,141,157],"interactions":[55],"spanning":[56],"local":[57],"congestion":[58],"patterns":[59],"global":[61],"functional":[62],"correlations,":[63],"(3)":[65],"inter-sample":[66,107],"variance":[68],"evolving":[70],"states.":[72],"To":[73],"address":[74],"these":[75],"limitations,":[76],"this":[77],"paper":[78],"proposes":[79],"MVA-DCNet":[80],"(Multi-View":[81],"Attention":[82],"Dilated":[83],"Convolutional":[84],"Network),":[85],"novel":[87],"deep":[88],"learning":[89],"architecture":[90,149],"incorporating":[91],"multidimensional":[93],"analysis":[95],"framework":[96],"that":[97],"systematically":[98,120],"examines":[99],"influence":[101],"mechanisms":[102],"through":[103,125],"three":[104,126],"complementary":[105],"perspectives:":[106],"variance,":[108],"intra-sequence":[109],"importance,":[111],"output":[113],"sequence":[114],"propagation.":[116],"The":[117],"proposed":[118],"model":[119],"addresses":[121],"data":[123,130],"innovative":[127],"mechanisms:":[128],"variance-aware":[129],"augmentation,":[131],"adaptive":[132],"attention,":[134],"loss":[137],"weighting.":[138],"For":[139],"enhanced":[140,151],"correlation":[142],"modeling,":[143],"we":[144],"develop":[145],"dilated":[147],"convolutional":[148],"with":[150,192],"receptive":[152],"field":[153],"coverage":[154],"pattern":[158],"recognition":[159],"capabilities.":[160],"Empirical":[161],"validation":[162],"on":[163],"two":[164],"urban":[165],"datasets":[167],"demonstrates":[168],"superior":[169],"efficacy":[170],"capturing":[172],"complex":[173],"evolution":[175],"patterns,":[176],"achieving":[177],"relative":[178],"reductions":[179],"12.7%":[181],"9.3%":[183],"Root":[185],"Mean":[186],"Square":[187],"Error":[188],"(RMSE)":[189],"respectively":[190],"compared":[191],"state-of-the-art":[193],"benchmarks.":[194]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-15T00:00:00"}
