{"id":"https://openalex.org/W2905424634","doi":"https://doi.org/10.1109/itsc.2018.8569964","title":"A Unified STARIMA based Model for Short-term Traffic Flow Prediction","display_name":"A Unified STARIMA based Model for Short-term Traffic Flow Prediction","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2905424634","doi":"https://doi.org/10.1109/itsc.2018.8569964","mag":"2905424634"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2018.8569964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569964","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":"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/A5010309828","display_name":"Peibo Duan","orcid":"https://orcid.org/0000-0002-0686-8404"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Peibo Duan","raw_affiliation_strings":["School of Computing and Communications, University of Technology, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Communications, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036000787","display_name":"Guoqiang Mao","orcid":"https://orcid.org/0000-0002-3598-4949"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guoqiang Mao","raw_affiliation_strings":["School of Computing and Communication, The University of Technology Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Communication, The University of Technology Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034502293","display_name":"Wenwei Yue","orcid":"https://orcid.org/0000-0002-1890-5911"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwei Yue","raw_affiliation_strings":["School of Information Engineering, Xi'dian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Xi'dian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054565395","display_name":"Shangbo Wang","orcid":"https://orcid.org/0000-0003-4347-6669"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shangbo Wang","raw_affiliation_strings":["School of Computing and Communications, University of Technology, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Communications, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010309828"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":0.7771,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.75905442,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"656","issue":null,"first_page":"1652","last_page":"1657"},"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":0.9965999722480774,"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":0.994700014591217,"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/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.8043192028999329},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6984592080116272},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6341559886932373},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6325452923774719},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5225409865379333},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4397476017475128},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4373907148838043},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.4233018159866333},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.41210103034973145},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41075950860977173},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33271467685699463},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2126205563545227},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16411903500556946},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11909130215644836}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.8043192028999329},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984592080116272},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6341559886932373},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6325452923774719},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5225409865379333},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4397476017475128},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4373907148838043},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.4233018159866333},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.41210103034973145},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41075950860977173},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33271467685699463},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2126205563545227},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16411903500556946},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11909130215644836},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/itsc.2018.8569964","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569964","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"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/133468","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/133468","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"mag:3041377147","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201902284272609343","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W32452329","https://openalex.org/W1610291649","https://openalex.org/W1952209694","https://openalex.org/W1979646154","https://openalex.org/W1991770012","https://openalex.org/W2057011654","https://openalex.org/W2111789455","https://openalex.org/W2150498351","https://openalex.org/W2160775398","https://openalex.org/W2293786206","https://openalex.org/W2343970958","https://openalex.org/W2564747559"],"related_works":["https://openalex.org/W3175321409","https://openalex.org/W4312561791","https://openalex.org/W2389894046","https://openalex.org/W2215717369","https://openalex.org/W2146461990","https://openalex.org/W4312309719","https://openalex.org/W4391216528","https://openalex.org/W2980748541","https://openalex.org/W4399581288","https://openalex.org/W4313123484"],"abstract_inverted_index":{"This":[0],"paper":[1,26],"proposes":[2],"a":[3,33,114,126,142,214],"unified":[4,127],"spatio-temporal":[5,44,53,111,139],"model":[6,128],"on":[7],"the":[8,42,58,82,108,120,122,131,136,164,177,185,210],"basis":[9],"of":[10,24,81,110,119,138,144,171,209],"STARIMA":[11,204],"(Space-Time":[12],"AutoRegressive":[13],"Integrated":[14,190],"Moving":[15,191],"Average)":[16,192],"for":[17,206],"short-term":[18],"road":[19,59,75,97,156],"traffic":[20,38,47,76,99,158,173],"prediction.":[21],"The":[22,52],"contributions":[23],"this":[25],"are":[27,148],"as":[28],"follows.":[29],"First,":[30],"we":[31],"develop":[32],"physically":[34,86],"intuitive":[35,87],"approach":[36,84,124,179],"to":[37,74,94,151,198],"prediction":[39],"that":[40,176,199],"captures":[41],"time-varying":[43,62,65],"correlation":[45,54,112,140],"between":[46],"at":[48],"different":[49,69,207],"measurement":[50],"points.":[51],"is":[55,194],"affected":[56],"by":[57,113,201],"network":[60],"topology,":[61],"speed,":[63],"and":[64,78,98,117,153,157,193,218],"trip":[66],"distribution.":[67],"Distinctly":[68],"from":[70],"previous":[71],"black-box":[72],"approaches":[73],"modeling":[77],"prediction,":[79],"parameters":[80,147],"proposed":[83,123,178],"have":[85],"meanings":[88],"which":[89,106,129],"make":[90],"them":[91],"readily":[92],"amenable":[93],"suit":[95],"changing":[96],"conditions.":[100],"Second,":[101],"unlike":[102],"some":[103],"existing":[104],"techniques":[105],"capture":[107],"variation":[109,137],"complete":[115],"redesign":[116],"calibration":[118],"model,":[121],"uses":[125],"incorporates":[130],"physical":[132],"factors":[133],"potentially":[134],"affecting":[135],"into":[141],"series":[143],"parameters.":[145],"These":[146],"relatively":[149],"easy":[150],"control":[152],"adjust":[154],"when":[155],"conditions":[159],"change,":[160],"thereby":[161],"greatly":[162],"reducing":[163],"computational":[165,217],"complexity.":[166,220],"Experiments":[167],"using":[168],"two":[169],"set":[170],"real":[172],"traces":[174],"demonstrate":[175],"has":[180],"superior":[181],"accuracy":[182],"compared":[183],"with":[184,213],"widely":[186],"used":[187],"ARIMA":[188],"(AutoRegressive":[189],"only":[195],"marginally":[196],"inferior":[197],"obtained":[200],"constructing":[202],"multiple":[203],"models":[205],"time":[208],"day,":[211],"however":[212],"much":[215],"reduced":[216],"implementation":[219]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}