{"id":"https://openalex.org/W2903775874","doi":"https://doi.org/10.1109/itsc.2018.8569276","title":"Traffic Flow Prediction with Parallel Data","display_name":"Traffic Flow Prediction with Parallel Data","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2903775874","doi":"https://doi.org/10.1109/itsc.2018.8569276","mag":"2903775874"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2018.8569276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100437870","display_name":"Yuanyuan Chen","orcid":"https://orcid.org/0000-0002-1886-3061"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Chen","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076992681","display_name":"Yisheng Lv","orcid":"https://orcid.org/0000-0002-7565-4979"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yisheng Lv","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112719601","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0002-0008-0659"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113600509","display_name":"Fei\u2013Yue Wang","orcid":"https://orcid.org/0000-0001-9185-3989"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei-Yue Wang","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"614","last_page":"619"},"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/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":1.0,"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":0.9944000244140625,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.7935053110122681},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.713775634765625},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6987047791481018},{"id":"https://openalex.org/keywords/advanced-traffic-management-system","display_name":"Advanced Traffic Management System","score":0.5757778882980347},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5554724335670471},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5549458265304565},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5414251685142517},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5372372269630432},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.5316957235336304},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5214468836784363},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49140679836273193},{"id":"https://openalex.org/keywords/traffic-volume","display_name":"Traffic volume","score":0.4834247827529907},{"id":"https://openalex.org/keywords/network-traffic-simulation","display_name":"Network traffic simulation","score":0.47900813817977905},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4740293323993683},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4412866532802582},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.43491053581237793},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.41535478830337524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40017372369766235},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.24503952264785767},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.21622738242149353},{"id":"https://openalex.org/keywords/network-traffic-control","display_name":"Network traffic control","score":0.1776358187198639},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1139320433139801},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10916277766227722},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09192299842834473},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.08617052435874939}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7935053110122681},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.713775634765625},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6987047791481018},{"id":"https://openalex.org/C42693407","wikidata":"https://www.wikidata.org/wiki/Q4686317","display_name":"Advanced Traffic Management System","level":3,"score":0.5757778882980347},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5554724335670471},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5549458265304565},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5414251685142517},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5372372269630432},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.5316957235336304},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5214468836784363},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49140679836273193},{"id":"https://openalex.org/C168443057","wikidata":"https://www.wikidata.org/wiki/Q7001223","display_name":"Traffic volume","level":2,"score":0.4834247827529907},{"id":"https://openalex.org/C94168897","wikidata":"https://www.wikidata.org/wiki/Q574324","display_name":"Network traffic simulation","level":4,"score":0.47900813817977905},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4740293323993683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4412866532802582},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.43491053581237793},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.41535478830337524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40017372369766235},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.24503952264785767},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.21622738242149353},{"id":"https://openalex.org/C201100257","wikidata":"https://www.wikidata.org/wiki/Q393287","display_name":"Network traffic control","level":3,"score":0.1776358187198639},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1139320433139801},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10916277766227722},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09192299842834473},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.08617052435874939},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2018.8569276","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W626441390","https://openalex.org/W2000474849","https://openalex.org/W2024896736","https://openalex.org/W2036785686","https://openalex.org/W2062067490","https://openalex.org/W2064675550","https://openalex.org/W2074387026","https://openalex.org/W2079554354","https://openalex.org/W2099471712","https://openalex.org/W2107878631","https://openalex.org/W2133747588","https://openalex.org/W2150010190","https://openalex.org/W2164268851","https://openalex.org/W2169559705","https://openalex.org/W2172064003","https://openalex.org/W2176149189","https://openalex.org/W2404399993","https://openalex.org/W2529827714","https://openalex.org/W2563738891","https://openalex.org/W2564701384","https://openalex.org/W2580360036","https://openalex.org/W2607909683","https://openalex.org/W2613331518","https://openalex.org/W2734479159","https://openalex.org/W2738419683","https://openalex.org/W2783478760","https://openalex.org/W2899676184","https://openalex.org/W2963709863","https://openalex.org/W2991327923","https://openalex.org/W4232929002","https://openalex.org/W4320013936","https://openalex.org/W6731621115","https://openalex.org/W6736821236","https://openalex.org/W6756534385"],"related_works":["https://openalex.org/W2587362999","https://openalex.org/W2009112536","https://openalex.org/W4315488634","https://openalex.org/W1550043390","https://openalex.org/W4308087771","https://openalex.org/W2478363130","https://openalex.org/W1994698836","https://openalex.org/W2288817554","https://openalex.org/W2905273075","https://openalex.org/W4285227736"],"abstract_inverted_index":{"Traffic":[0],"prediction":[1,14,48,91,101,114],"is":[2,15,58],"an":[3,120],"elemental":[4],"function":[5],"of":[6,16,30,64,77,84,95,155],"Intelligent":[7],"Transportation":[8],"Systems,":[9],"and":[10,12,24,33,53,81,102,112,129],"accurate":[11,65],"timely":[13],"great":[17],"significance":[18],"to":[19,60,73,88,105,125],"both":[20],"traffic":[21,44,66,79,86,90,100,108,113,127,137,144,156],"management":[22],"agencies":[23],"individual":[25],"drivers.":[26],"With":[27],"the":[28,103,153],"development":[29],"deep":[31,36],"learning":[32],"big":[34],"data,":[35,55,128],"neural":[37],"networks":[38,124],"(DNN)":[39],"achieve":[40],"superior":[41],"performances":[42],"in":[43],"prediction.":[45,138,158],"Developing":[46],"DNN":[47],"models":[49,111,115],"needs":[50],"large":[51,62,82],"scale":[52],"diverse":[54],"however,":[56],"it":[57],"costly":[59],"collect":[61],"volume":[63,76,83],"data.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"propose":[72],"use":[74,119],"small":[75],"real":[78,143],"data":[80,87,109],"synthetic":[85],"developing":[89],"models.":[92],"The":[93],"evolving":[94],"parallel":[96],"system":[97],"paradigm":[98],"for":[99,136],"algorithm":[104],"incrementally":[106],"train":[107],"generation":[110],"are":[116],"presented.":[117],"We":[118],"improved":[121],"generative":[122],"adversarial":[123],"generate":[126],"a":[130,142],"stacked":[131],"long":[132],"short-term":[133],"memory":[134],"model":[135],"Experimental":[139],"results":[140],"on":[141],"dataset":[145],"demonstrate":[146],"that":[147],"our":[148],"method":[149],"can":[150],"significantly":[151],"improve":[152],"performance":[154],"flow":[157]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}