{"id":"https://openalex.org/W4407155109","doi":"https://doi.org/10.1109/tits.2025.3533560","title":"A Sparse Cross Attention-Based Graph Convolution Network With Auxiliary Information Awareness for Traffic Flow Prediction","display_name":"A Sparse Cross Attention-Based Graph Convolution Network With Auxiliary Information Awareness for Traffic Flow Prediction","publication_year":2025,"publication_date":"2025-02-04","ids":{"openalex":"https://openalex.org/W4407155109","doi":"https://doi.org/10.1109/tits.2025.3533560"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3533560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3533560","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041606758","display_name":"Lingqiang Chen","orcid":"https://orcid.org/0000-0001-5379-0972"},"institutions":[{"id":"https://openalex.org/I106079672","display_name":"Hebei University of Engineering","ror":"https://ror.org/036h65h05","country_code":"CN","type":"education","lineage":["https://openalex.org/I106079672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lingqiang Chen","raw_affiliation_strings":["School of Information and Electrical Engineering, Hebei University of Engineering, Handan, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electrical Engineering, Hebei University of Engineering, Handan, China","institution_ids":["https://openalex.org/I106079672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038174569","display_name":"Qinglin Zhao","orcid":"https://orcid.org/0000-0003-4873-5631"},"institutions":[{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Qinglin Zhao","raw_affiliation_strings":["School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China","institution_ids":["https://openalex.org/I111950717"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028229932","display_name":"Guanghui Li","orcid":"https://orcid.org/0000-0002-6884-5670"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghui Li","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081318069","display_name":"MengChu Zhou","orcid":"https://orcid.org/0000-0002-5408-8752"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengchu Zhou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038432832","display_name":"Chenglong Dai","orcid":"https://orcid.org/0000-0002-1908-0026"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglong Dai","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108296537","display_name":"Yiming Feng","orcid":"https://orcid.org/0000-0003-0837-4069"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming Feng","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390771","display_name":"Xiaowei Liu","orcid":"https://orcid.org/0000-0003-2074-3760"},"institutions":[{"id":"https://openalex.org/I106079672","display_name":"Hebei University of Engineering","ror":"https://ror.org/036h65h05","country_code":"CN","type":"education","lineage":["https://openalex.org/I106079672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Liu","raw_affiliation_strings":["School of Information and Electrical Engineering, Hebei University of Engineering, Handan, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electrical Engineering, Hebei University of Engineering, Handan, China","institution_ids":["https://openalex.org/I106079672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028836596","display_name":"Jinjiang Li","orcid":"https://orcid.org/0000-0002-2080-8678"},"institutions":[{"id":"https://openalex.org/I106079672","display_name":"Hebei University of Engineering","ror":"https://ror.org/036h65h05","country_code":"CN","type":"education","lineage":["https://openalex.org/I106079672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinjiang Li","raw_affiliation_strings":["School of Information and Electrical Engineering, Hebei University of Engineering, Handan, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electrical Engineering, Hebei University of Engineering, Handan, China","institution_ids":["https://openalex.org/I106079672"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5041606758"],"corresponding_institution_ids":["https://openalex.org/I106079672"],"apc_list":null,"apc_paid":null,"fwci":4.7876,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.93761141,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"26","issue":"3","first_page":"3210","last_page":"3222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10320","display_name":"Neural Networks and Applications","score":0.9523000121116638,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9473999738693237,"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":0.6211193203926086},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5186871290206909},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46432796120643616},{"id":"https://openalex.org/keywords/control-flow-graph","display_name":"Control flow graph","score":0.4273895025253296},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4112270176410675},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3637998700141907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3495732843875885},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3350796699523926},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.21983811259269714},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10373520851135254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6211193203926086},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5186871290206909},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46432796120643616},{"id":"https://openalex.org/C27458966","wikidata":"https://www.wikidata.org/wiki/Q1187693","display_name":"Control flow graph","level":2,"score":0.4273895025253296},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4112270176410675},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3637998700141907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3495732843875885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3350796699523926},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.21983811259269714},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10373520851135254}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3533560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3533560","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G264105064","display_name":null,"funder_award_id":"0093/2022/A2","funder_id":"https://openalex.org/F4320321655","funder_display_name":"Science and Technology Development Fund"},{"id":"https://openalex.org/G2908032384","display_name":null,"funder_award_id":"62372214","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5297886466","display_name":null,"funder_award_id":"0008/2022/AGJ","funder_id":"https://openalex.org/F4320321655","funder_display_name":"Science and Technology Development Fund"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321655","display_name":"Science and Technology Development Fund","ror":"https://ror.org/044vr6g03"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2080731889","https://openalex.org/W2528639018","https://openalex.org/W2756203131","https://openalex.org/W2940640769","https://openalex.org/W2950817888","https://openalex.org/W2962790412","https://openalex.org/W2965341826","https://openalex.org/W2972752351","https://openalex.org/W3004515714","https://openalex.org/W3026400623","https://openalex.org/W3092527624","https://openalex.org/W3094910090","https://openalex.org/W3123909522","https://openalex.org/W3126367810","https://openalex.org/W3143418053","https://openalex.org/W3171958173","https://openalex.org/W3174022889","https://openalex.org/W3209643259","https://openalex.org/W4205945573","https://openalex.org/W4212805305","https://openalex.org/W4283739673","https://openalex.org/W4286568257","https://openalex.org/W4291109995","https://openalex.org/W4294310652","https://openalex.org/W4312266567","https://openalex.org/W4322766466","https://openalex.org/W4376456657","https://openalex.org/W4382239616","https://openalex.org/W4385245566","https://openalex.org/W4390465641","https://openalex.org/W4390492464","https://openalex.org/W4390547377","https://openalex.org/W4390604340","https://openalex.org/W4395702745"],"related_works":["https://openalex.org/W4387838477","https://openalex.org/W2067193074","https://openalex.org/W2182785089","https://openalex.org/W4312178642","https://openalex.org/W2375093801","https://openalex.org/W3107426390","https://openalex.org/W1534368937","https://openalex.org/W2964145245","https://openalex.org/W2595205408","https://openalex.org/W2422195048"],"abstract_inverted_index":{"Deep":[0],"graph":[1,50,88],"convolutional":[2,89],"networks":[3],"(GCNs)":[4],"have":[5],"shown":[6],"promising":[7],"performance":[8,201],"in":[9,125],"traffic":[10,42,59,119,145,154,183,194],"prediction":[11,187],"tasks,":[12],"but":[13],"their":[14],"practical":[15],"deployment":[16],"on":[17,40,191,222],"resource-constrained":[18],"devices":[19],"faces":[20],"challenges.":[21],"First,":[22],"few":[23],"models":[24],"consider":[25],"the":[26,45,56,144,150,161,173],"potential":[27],"influence":[28],"of":[29,48,58,153,165],"historical":[30,93,122],"and":[31,38,84,106,217],"future":[32,95,176],"auxiliary":[33,80,100],"information,":[34],"such":[35],"as":[36,156],"weather":[37],"holidays,":[39],"complex":[41],"patterns.":[43],"Second,":[44],"computational":[46,163,170],"complexity":[47,164],"dynamic":[49,130],"convolution":[51],"operations":[52],"grows":[53],"quadratically":[54],"with":[55,121,181],"number":[57],"nodes,":[60],"limiting":[61],"model":[62,74],"scalability.":[63],"To":[64],"address":[65],"these":[66],"challenges,":[67],"this":[68],"study":[69],"proposes":[70],"a":[71,85,114,157],"deep":[72],"encoder-decoder":[73],"named":[75],"AIMSAN,":[76],"which":[77],"comprises":[78],"an":[79],"information-aware":[81],"module":[82],"(AIM)":[83],"sparse":[86],"cross-attention-based":[87],"network":[90],"(SAN).":[91],"From":[92],"or":[94],"perspectives,":[96],"AIM":[97],"prunes":[98],"multi-attribute":[99],"data":[101,120,124,178,184],"into":[102,109],"diverse":[103],"time":[104,214,219],"frames,":[105],"embeds":[107],"them":[108],"one":[110],"tensor.":[111],"SAN":[112],"employs":[113],"cross-attention":[115],"mechanism":[116],"to":[117,138,159,185,203],"merge":[118],"embedded":[123,177],"each":[126],"encoder":[127],"layer,":[128,175],"forming":[129],"adjacency":[131],"matrices.":[132],"Subsequently,":[133],"it":[134],"applies":[135],"diffusion":[136],"GCN":[137],"capture":[139],"rich":[140],"spatial-temporal":[141],"dynamics":[142],"from":[143],"data.":[146],"Additionally,":[147],"AIMSAN":[148,198],"utilizes":[149],"spatial":[151],"sparsity":[152],"nodes":[155],"mask":[158],"mitigate":[160],"quadratic":[162],"SAN,":[166],"thereby":[167],"improving":[168],"overall":[169],"efficiency.":[171],"In":[172],"decoder":[174],"are":[179],"fused":[180],"feed-forward":[182],"generate":[186],"results.":[188],"Experimental":[189],"evaluations":[190],"three":[192],"public":[193],"datasets":[195],"demonstrate":[196],"that":[197],"achieves":[199],"competitive":[200],"compared":[202],"state-of-the-art":[204],"algorithms,":[205],"while":[206],"reducing":[207],"GPU":[208],"memory":[209],"consumption":[210],"by":[211,215,220],"41.24%,":[212],"training":[213],"62.09%,":[216],"validation":[218],"65.17%":[221],"average.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
