{"id":"https://openalex.org/W3000140956","doi":"https://doi.org/10.1109/soli48380.2019.8955102","title":"Short Term Traffic Flow Forecast Based on CM-GRU Networks","display_name":"Short Term Traffic Flow Forecast Based on CM-GRU Networks","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3000140956","doi":"https://doi.org/10.1109/soli48380.2019.8955102","mag":"3000140956"},"language":"en","primary_location":{"id":"doi:10.1109/soli48380.2019.8955102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/soli48380.2019.8955102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","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/A5000132909","display_name":"Zhongzheng Guo","orcid":null},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongzheng Guo","raw_affiliation_strings":["the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019721709","display_name":"Weifeng Zhong","orcid":"https://orcid.org/0000-0003-4200-9065"},"institutions":[{"id":"https://openalex.org/I100188998","display_name":"Harbin University of Science and Technology","ror":"https://ror.org/04e6y1282","country_code":"CN","type":"education","lineage":["https://openalex.org/I100188998"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifeng Zhong","raw_affiliation_strings":["Institute of Automation, Harbin University of Science And Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Harbin University of Science And Technology, Harbin, China","institution_ids":["https://openalex.org/I100188998"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042359485","display_name":"Fenghua Zhu","orcid":"https://orcid.org/0000-0003-2886-6968"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fenghua Zhu","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100777893","display_name":"Xiaoshuang Li","orcid":"https://orcid.org/0000-0002-0773-6462"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoshuang Li","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei-Yue Wang","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088979194","display_name":"Gang Xiong","orcid":"https://orcid.org/0000-0002-4303-5559"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Xiong","raw_affiliation_strings":["State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"163","last_page":"168"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9933000206947327,"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"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9912999868392944,"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":0.7381241321563721},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.7264307141304016},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5976883769035339},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5778766870498657},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5521687865257263},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4985952377319336},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4916287064552307},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4880429804325104},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4314190149307251},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43128615617752075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4213923215866089},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4121379852294922},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.35561951994895935},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32332879304885864},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1418740153312683},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.10092654824256897},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08204418420791626},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07952290773391724}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7381241321563721},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.7264307141304016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5976883769035339},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5778766870498657},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5521687865257263},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4985952377319336},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4916287064552307},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4880429804325104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4314190149307251},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43128615617752075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4213923215866089},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4121379852294922},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35561951994895935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32332879304885864},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1418740153312683},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.10092654824256897},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08204418420791626},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07952290773391724},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/soli48380.2019.8955102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/soli48380.2019.8955102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W626441390","https://openalex.org/W1924770834","https://openalex.org/W1996058270","https://openalex.org/W2036109700","https://openalex.org/W2036785686","https://openalex.org/W2073640212","https://openalex.org/W2083238230","https://openalex.org/W2108196201","https://openalex.org/W2160507653","https://openalex.org/W2165991108","https://openalex.org/W2171234954","https://openalex.org/W2189149359","https://openalex.org/W2557283755","https://openalex.org/W2563738891","https://openalex.org/W2572939427","https://openalex.org/W2573587735","https://openalex.org/W2593182953","https://openalex.org/W2593809812","https://openalex.org/W2596628535","https://openalex.org/W2748105865","https://openalex.org/W2750716377","https://openalex.org/W2775717462","https://openalex.org/W2777363140","https://openalex.org/W2778498877","https://openalex.org/W2782495288","https://openalex.org/W2803538925","https://openalex.org/W2803677510","https://openalex.org/W2804073446","https://openalex.org/W2805085159","https://openalex.org/W2885178111","https://openalex.org/W2896314053","https://openalex.org/W2910197777","https://openalex.org/W2916752133","https://openalex.org/W2918600339","https://openalex.org/W2921685418","https://openalex.org/W2938342315","https://openalex.org/W4320013936","https://openalex.org/W6640212811","https://openalex.org/W6687141316","https://openalex.org/W6731432862"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2804383999","https://openalex.org/W1987895267"],"abstract_inverted_index":{"Intelligent":[0],"transportation":[1],"systems":[2],"(ITS)":[3],"have":[4],"developed":[5],"for":[6],"a":[7,86,104,112,137],"long":[8],"time.":[9],"The":[10,32,78],"rise":[11],"of":[12,19,43,57,88,100,115],"deep":[13,76],"learning":[14],"has":[15,103],"brought":[16],"new":[17],"vitality":[18],"the":[20,41,49,55,58,81,98,116,120,129,149],"ITS.":[21],"However,":[22],"traffic":[23,44,51,59,70],"flow":[24,45,60,71,125],"data":[25,33,126],"is":[26],"usually":[27],"time-correlated":[28],"and":[29,93],"highly":[30],"randomized.":[31],"distribution":[34],"will":[35],"also":[36,142],"change":[37],"dynamically.":[38],"To":[39],"actualize":[40],"forecasting":[42],"accurately,":[46],"we":[47],"use":[48],"historical":[50],"information":[52],"to":[53],"predict":[54],"messages":[56],"at":[61],"any":[62],"time":[63],"interval.":[64],"This":[65],"paper":[66,110,134],"proposes":[67],"an":[68],"efficient":[69],"forecast":[72],"architecture":[73],"based":[74],"on":[75,107,124],"learning.":[77],"method":[79,130],"combines":[80],"gated":[82],"recurrent":[83,89],"unit":[84],"(GRU,":[85],"type":[87],"neural":[90],"network)":[91],"layers":[92],"one-dimension":[94],"convolution":[95],"layers.":[96],"Since":[97],"performance":[99],"these":[101],"models":[102],"strong":[105],"dependence":[106],"hyper-parameters,":[108],"this":[109,133],"conducts":[111],"large-scale":[113],"search":[114],"hyper-parameter":[117],"space.":[118],"At":[119],"same":[121],"time,":[122],"experiments":[123],"show":[127,143],"that":[128],"proposed":[131],"in":[132],"can":[135],"achieve":[136],"better":[138],"prediction":[139],"accuracy.":[140],"Experiments":[141],"lower":[144],"test":[145],"errors":[146],"compared":[147],"with":[148],"existing":[150],"approaches.":[151]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}