{"id":"https://openalex.org/W4393248060","doi":"https://doi.org/10.48550/arxiv.2403.17753","title":"CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream\n Enhanced Rectified Transformer Model","display_name":"CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream\n Enhanced Rectified Transformer Model","publication_year":2024,"publication_date":"2024-03-26","ids":{"openalex":"https://openalex.org/W4393248060","doi":"https://doi.org/10.48550/arxiv.2403.17753"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.17753","pdf_url":"http://arxiv.org/pdf/2403.17753","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2403.17753","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114140318","display_name":"Zhiqi Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Zhiqi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073230220","display_name":"Michael G.H. Bell","orcid":"https://orcid.org/0000-0001-8137-065X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bell, Michael G. H.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040254887","display_name":"Ze Wang","orcid":"https://orcid.org/0000-0002-4732-6249"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ze","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001438153","display_name":"Glenn Geers","orcid":"https://orcid.org/0000-0002-3306-7290"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Geers, D. Glenn","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109696076","display_name":"Xusheng Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Xusheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5015817857","display_name":"Junbin Gao","orcid":"https://orcid.org/0000-0001-9803-0256"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Junbin","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.906977,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":77,"max":88},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9938,"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":0.9938,"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":0.9156,"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"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6311251},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47489324},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.45817706},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32278383},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.30270985},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20784536},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.16851795},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.15298274},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.17753","pdf_url":"http://arxiv.org/pdf/2403.17753","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.17753","pdf_url":"http://arxiv.org/pdf/2403.17753","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391913857","https://openalex.org/W2864363823","https://openalex.org/W2748952813","https://openalex.org/W2478288626","https://openalex.org/W2390279801","https://openalex.org/W2382290278","https://openalex.org/W2376932109","https://openalex.org/W2358668433","https://openalex.org/W2350741829","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Accurate,":[0],"and":[1,16,31,38,41,76,101,104],"effective":[2],"traffic":[3,9,14,98,144],"forecasting":[4],"is":[5],"vital":[6],"for":[7,96],"smart":[8],"systems,":[10],"crucial":[11],"in":[12],"urban":[13],"planning":[15],"management.":[17],"Current":[18],"Spatio-Temporal":[19],"Transformer":[20,57],"models,":[21],"despite":[22],"their":[23],"prediction":[24],"capabilities,":[25],"struggle":[26],"with":[27],"balancing":[28],"computational":[29,87],"efficiency":[30],"accuracy,":[32,137],"favoring":[33],"global":[34],"over":[35],"local":[36,94],"information,":[37],"handling":[39],"spatial":[40,103],"temporal":[42,105],"data":[43],"separately,":[44],"limiting":[45],"insight":[46],"into":[47],"complex":[48],"interactions.":[49],"We":[50],"introduce":[51],"the":[52,127,134],"Criss-Crossed":[53],"Dual-Stream":[54],"Enhanced":[55,65,70,77],"Rectified":[56,66,71,78],"model":[58],"(CCDSReFormer),":[59],"which":[60],"includes":[61],"three":[62],"innovative":[63],"modules:":[64],"Spatial":[67],"Self-attention":[68,74,80],"(ReSSA),":[69],"Delay":[72],"Aware":[73],"(ReDASA),":[75],"Temporal":[79],"(ReTSA).":[81],"These":[82],"modules":[83],"aim":[84],"to":[85,142],"lower":[86],"needs":[88],"via":[89],"sparse":[90],"attention,":[91],"focus":[92],"on":[93,114,133],"information":[95],"better":[97],"dynamics":[99],"understanding,":[100],"merge":[102],"insights":[106],"through":[107],"a":[108],"unique":[109],"learning":[110],"method.":[111],"Extensive":[112],"tests":[113],"six":[115],"real-world":[116],"datasets":[117],"highlight":[118],"CCDSReFormer's":[119],"superior":[120],"performance.":[121],"An":[122],"ablation":[123],"study":[124],"also":[125],"confirms":[126],"significant":[128],"impact":[129],"of":[130],"each":[131],"component":[132],"model's":[135,140],"predictive":[136],"showcasing":[138],"our":[139],"ability":[141],"forecast":[143],"flow":[145],"effectively.":[146]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4393248060","counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-04-23T21:51:11.232508","created_date":"2024-03-28"}