{"id":"https://openalex.org/W4406457590","doi":"https://doi.org/10.1109/tetci.2025.3525656","title":"PCR: A Parallel Convolution Residual Network for Traffic Flow Prediction","display_name":"PCR: A Parallel Convolution Residual Network for Traffic Flow Prediction","publication_year":2025,"publication_date":"2025-01-16","ids":{"openalex":"https://openalex.org/W4406457590","doi":"https://doi.org/10.1109/tetci.2025.3525656"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2025.3525656","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3525656","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","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/A5048157278","display_name":"C. C. Zuo","orcid":"https://orcid.org/0009-0005-4596-1790"},"institutions":[{"id":"https://openalex.org/I2800393352","display_name":"China Tourism Academy","ror":"https://ror.org/01k4abj61","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800393352"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Changqi Zuo","raw_affiliation_strings":["Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0005-4596-1790","affiliations":[{"raw_affiliation_string":"Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, Chongqing, China","institution_ids":["https://openalex.org/I2800393352"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437250","display_name":"Xu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I2800393352","display_name":"China Tourism Academy","ror":"https://ror.org/01k4abj61","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800393352"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Zhang","raw_affiliation_strings":["Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7051-2736","affiliations":[{"raw_affiliation_string":"Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, Chongqing, China","institution_ids":["https://openalex.org/I2800393352"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034900420","display_name":"Gen Zhao","orcid":"https://orcid.org/0009-0005-5623-5823"},"institutions":[{"id":"https://openalex.org/I4210160019","display_name":"Chongqing Municipal Health Commission","ror":"https://ror.org/04ce5fg13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210157972","https://openalex.org/I4210160019"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gen Zhao","raw_affiliation_strings":["Chongqing Planning Exhibition Gallery, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0005-5623-5823","affiliations":[{"raw_affiliation_string":"Chongqing Planning Exhibition Gallery, Chongqing, China","institution_ids":["https://openalex.org/I4210160019"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050528126","display_name":"Liang Yan","orcid":"https://orcid.org/0000-0002-1941-8429"},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Yan","raw_affiliation_strings":["Key Laboratory of Monitoring, Evaluation and Early Warning of Territorial Spatial Planning Implementation, Ministry of Natural Resources, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Monitoring, Evaluation and Early Warning of Territorial Spatial Planning Implementation, Ministry of Natural Resources, Beijing, China","institution_ids":["https://openalex.org/I211433327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5048157278"],"corresponding_institution_ids":["https://openalex.org/I2800393352"],"apc_list":null,"apc_paid":null,"fwci":34.1543,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.99904781,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"9","issue":"4","first_page":"3072","last_page":"3083"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.982699990272522,"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":0.982699990272522,"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":0.9699000120162964,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.926800012588501,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7725825905799866},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.615592360496521},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5578299760818481},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.42522573471069336},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.310060977935791},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2953079342842102},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2675899863243103},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10470524430274963}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7725825905799866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.615592360496521},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5578299760818481},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.42522573471069336},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.310060977935791},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2953079342842102},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2675899863243103},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10470524430274963}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2025.3525656","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3525656","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1569376345","https://openalex.org/W1996058270","https://openalex.org/W2089058212","https://openalex.org/W2105482032","https://openalex.org/W2194775991","https://openalex.org/W2528639018","https://openalex.org/W2756203131","https://openalex.org/W2788134583","https://openalex.org/W2890385714","https://openalex.org/W2899443545","https://openalex.org/W2903871660","https://openalex.org/W2904813135","https://openalex.org/W2905442144","https://openalex.org/W2919115771","https://openalex.org/W2921685418","https://openalex.org/W2943201207","https://openalex.org/W2950635152","https://openalex.org/W2962790412","https://openalex.org/W3035338169","https://openalex.org/W3037233197","https://openalex.org/W3156972038","https://openalex.org/W3193100408","https://openalex.org/W3193281533","https://openalex.org/W4213088607","https://openalex.org/W4225157025","https://openalex.org/W4285262037","https://openalex.org/W4293704603","https://openalex.org/W4310790298","https://openalex.org/W4313201657","https://openalex.org/W4313855753","https://openalex.org/W4321021801","https://openalex.org/W4322101447","https://openalex.org/W4366452034","https://openalex.org/W4366779109","https://openalex.org/W4379876193","https://openalex.org/W4382239616","https://openalex.org/W4382240004","https://openalex.org/W4387846311","https://openalex.org/W4388283607","https://openalex.org/W4388505307","https://openalex.org/W4402260442","https://openalex.org/W6628877408","https://openalex.org/W6746015598"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2560215812","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2949601986"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,65,161],"prediction":[2],"is":[3,133],"crucial":[4],"in":[5,42],"smart":[6],"cities":[7],"and":[8,20,80,146,165],"traffic":[9,64,160],"management,":[10],"yet":[11],"it":[12],"presents":[13],"challenges":[14],"due":[15],"to":[16,33,75,92,100,141,152],"intricate":[17],"spatial-temporal":[18],"dependencies":[19],"external":[21,102,118],"factors.":[22],"Most":[23],"existing":[24],"research":[25],"relied":[26],"on":[27,158],"a":[28,70,94,123,136,147],"traditional":[29],"data":[30,72],"selection":[31,73],"approach":[32],"represent":[34,111],"temporal":[35,78],"dependence.":[36,156],"However,":[37],"only":[38],"considering":[39],"spatial":[40,144,155],"dependence":[41,145],"adjacent":[43],"or":[44],"distant":[45],"regions":[46],"limits":[47],"the":[48,112,169,173,177],"performance.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53,68,82,98,121],"propose":[54,99],"an":[55,84],"end-to-end":[56],"Parallel":[57],"Convolution":[58],"Residual":[59],"network":[60,126],"(PCR)":[61],"for":[62],"grid-based":[63],"prediction.":[66],"First,":[67],"introduce":[69],"novel":[71],"strategy":[74,87],"capture":[76],"more":[77],"dependence,":[79],"then":[81],"implement":[83],"early":[85],"fusion":[86],"without":[88],"any":[89],"additional":[90],"operations":[91],"obtain":[93],"lighter":[95],"model.":[96],"Second,":[97],"extract":[101,142,153],"features":[103,129],"with":[104,127,176],"feature":[105],"embedding":[106],"matrix":[107],"operations,":[108],"which":[109,132],"can":[110],"interrelationships":[113],"between":[114],"different":[115],"kinds":[116],"of":[117,135],"data.":[119],"Finally,":[120],"build":[122],"parallel":[124],"residual":[125,138,149],"concatenated":[128],"as":[130],"input,":[131],"composed":[134],"standard":[137],"net":[139,150],"(SRN)":[140],"short":[143],"dilated":[148],"(DRN)":[151],"long":[154],"Experiments":[157],"three":[159],"datasets":[162],"TaxiBJ,":[163],"BikeNYC,":[164],"TaxiCQ":[166],"exhibit":[167],"that":[168],"proposed":[170],"method":[171],"outperforms":[172],"state-of-the-art":[174],"models":[175],"most":[178],"minor":[179],"parameters.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":30}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
