{"id":"https://openalex.org/W2798466145","doi":"https://doi.org/10.1109/icoin.2018.8343075","title":"Improved UGRNN for short-term traffic flow prediction with multi-feature sequence inputs","display_name":"Improved UGRNN for short-term traffic flow prediction with multi-feature sequence inputs","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2798466145","doi":"https://doi.org/10.1109/icoin.2018.8343075","mag":"2798466145"},"language":"en","primary_location":{"id":"doi:10.1109/icoin.2018.8343075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin.2018.8343075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Information Networking (ICOIN)","raw_type":"proceedings-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/A5006388638","display_name":"Jiabin Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiabin Qu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing 100876, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018769767","display_name":"Xinyu Gu","orcid":"https://orcid.org/0000-0001-6762-7463"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Gu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing 100876, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013925708","display_name":"Lin Zhang","orcid":"https://orcid.org/0000-0001-9544-0399"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing 100876, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing 100876, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006388638"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":1.5506,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.82438884,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"17"},"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":0.9961000084877014,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.8147507905960083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7610310316085815},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6369664072990417},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6077777743339539},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5643221735954285},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.558586597442627},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5558969974517822},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.50006103515625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4965556263923645},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4896445870399475},{"id":"https://openalex.org/keywords/long-term-prediction","display_name":"Long-term prediction","score":0.4821486175060272},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45092105865478516},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.45029565691947937},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.42435234785079956},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4169638156890869},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41498199105262756},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3398120105266571},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.26189351081848145},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1506580114364624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08620795607566833}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.8147507905960083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7610310316085815},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6369664072990417},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6077777743339539},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5643221735954285},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.558586597442627},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5558969974517822},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.50006103515625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4965556263923645},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4896445870399475},{"id":"https://openalex.org/C2776537626","wikidata":"https://www.wikidata.org/wiki/Q4047883","display_name":"Long-term prediction","level":2,"score":0.4821486175060272},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45092105865478516},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.45029565691947937},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.42435234785079956},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4169638156890869},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41498199105262756},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3398120105266571},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.26189351081848145},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1506580114364624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08620795607566833},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","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/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icoin.2018.8343075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin.2018.8343075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Information Networking (ICOIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1958929917","https://openalex.org/W1973943669","https://openalex.org/W2036785686","https://openalex.org/W2079662306","https://openalex.org/W2082533141","https://openalex.org/W2131767615","https://openalex.org/W2150010190","https://openalex.org/W2392719515","https://openalex.org/W2533328922","https://openalex.org/W2535394993","https://openalex.org/W2557270725","https://openalex.org/W2572939427","https://openalex.org/W2586538484","https://openalex.org/W2950059857","https://openalex.org/W6659849045","https://openalex.org/W6729992640"],"related_works":["https://openalex.org/W3135881084","https://openalex.org/W2380590035","https://openalex.org/W2351712633","https://openalex.org/W4388984322","https://openalex.org/W4285509495","https://openalex.org/W1509694164","https://openalex.org/W4396569707","https://openalex.org/W4378983035","https://openalex.org/W2969222287","https://openalex.org/W600497038"],"abstract_inverted_index":{"As":[0],"we":[1,92],"all":[2],"know,":[3],"an":[4],"Intelligent":[5],"Transportation":[6],"System":[7],"(ITS)":[8],"will":[9],"be":[10],"built":[11],"more":[12,14],"and":[13],"perfect":[15],"in":[16,107],"the":[17,36,57,119],"future.":[18],"In":[19,89],"order":[20,108],"to":[21,28,109],"achieve":[22],"this":[23,90,111],"goal,":[24],"it":[25,54],"is":[26],"essential":[27],"predict":[29],"short-term":[30],"traffic":[31,39,69],"flow":[32,70],"accurately.":[33],"Because":[34],"of":[35,38,59,74,80],"nonlinearity":[37],"flow,":[40],"classic":[41],"linear":[42],"models":[43,64,82],"including":[44],"auto":[45],"regressive":[46],"integrated":[47],"moving":[48],"average":[49],"(ARIMA)":[50],"can":[51,83],"not":[52],"fit":[53],"well.":[55],"With":[56],"development":[58],"deep":[60],"learning,":[61],"some":[62],"advanced":[63],"have":[65],"been":[66],"used":[67,117],"for":[68],"prediction.":[71],"The":[72],"accuracy":[73],"prediction":[75],"has":[76],"improved,":[77],"but":[78],"none":[79],"these":[81],"handle":[84],"multi-feature":[85],"sequence":[86],"inputs":[87],"problem.":[88,112],"paper,":[91],"propose":[93],"a":[94],"improved":[95],"structure":[96],"called":[97],"Combined-UGRNN":[98,120],"based":[99],"on":[100],"Update":[101],"Gate":[102],"Recurrent":[103],"Neural":[104],"Network":[105],"(UGRNN)":[106],"solve":[110],"Compared":[113],"with":[114],"other":[115],"widely":[116],"algorithms,":[118],"achieves":[121],"highest":[122],"accuracy.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}