{"id":"https://openalex.org/W3026663574","doi":"https://doi.org/10.1145/3384613.3384631","title":"A spatial-temporal framework including traffic diffusion for short-term traffic prediction","display_name":"A spatial-temporal framework including traffic diffusion for short-term traffic prediction","publication_year":2020,"publication_date":"2020-02-14","ids":{"openalex":"https://openalex.org/W3026663574","doi":"https://doi.org/10.1145/3384613.3384631","mag":"3026663574"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3384613.3384631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5082602991","display_name":"Xuefang Zhao","orcid":"https://orcid.org/0000-0003-4036-9577"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefang Zhao","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School ShenZhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School ShenZhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100325046","display_name":"Dapeng Zhang","orcid":"https://orcid.org/0000-0001-9616-8059"},"institutions":[],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dapeng Zhang","raw_affiliation_strings":["Shenzhen e-Traffic Technology Co., Ltd ShenZhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen e-Traffic Technology Co., Ltd ShenZhen, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100323973","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0002-5221-1868"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School ShenZhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School ShenZhen, China","institution_ids":["https://openalex.org/I4210114105"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.332,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.331851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":60,"max":69},"biblio":{"volume":null,"issue":null,"first_page":"136","last_page":"139"},"is_retracted":false,"is_paratext":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":0.9972,"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":0.9963,"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":[],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.75022924},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.67312056},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.55691874},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.46253848},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32747233},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.20634627},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11871365},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06405783},{"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3384613.3384631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.49,"display_name":"Sustainable cities and communities"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":13,"referenced_works":["https://openalex.org/W2002033255","https://openalex.org/W2011636111","https://openalex.org/W2029050814","https://openalex.org/W2036785686","https://openalex.org/W2040895929","https://openalex.org/W2066636486","https://openalex.org/W2090192376","https://openalex.org/W2163605009","https://openalex.org/W2491772710","https://openalex.org/W2596628535","https://openalex.org/W2952740813","https://openalex.org/W626441390","https://openalex.org/W744439916"],"related_works":["https://openalex.org/W3164102603","https://openalex.org/W2972412491","https://openalex.org/W2889205661","https://openalex.org/W2374017701","https://openalex.org/W2372022541","https://openalex.org/W2363789696","https://openalex.org/W2363207358","https://openalex.org/W2170010002","https://openalex.org/W2056851291","https://openalex.org/W1519398290"],"abstract_inverted_index":{"With":[0],"the":[1,29,63,69,83,114,128],"increasing":[2],"popularity":[3],"of":[4,31,37,43,130],"Intelligent":[5],"Transportation":[6],"Systems,":[7],"how":[8],"to":[9,27,61,81,101],"achieve":[10],"accurate":[11],"and":[12,19,86,108],"real-time":[13],"traffic":[14,32,44,94,131,137],"prediction":[15,33,103],"has":[16,133],"become":[17],"more":[18,20],"important.":[21],"In":[22],"this":[23],"paper,":[24],"we":[25],"intend":[26],"improve":[28],"accuracy":[30],"by":[34,68],"appropriate":[35],"integration":[36],"diffusion":[38,132],"process.":[39],"The":[40],"spatial-temporal":[41],"features":[42,65],"flow":[45],"are":[46,79,98,111],"captured":[47],"within":[48],"an":[49],"encoder-decoder":[50,118],"framework.":[51,119],"Specifically,":[52],"(1)":[53],"a":[54,123],"1-dimension":[55],"Convolutional":[56],"Network":[57],"(CNN)":[58],"is":[59],"exploited":[60],"capture":[62],"spatial":[64],"when":[66],"fed":[67],"congestion":[70],"matrix;":[71],"(2)":[72],"two":[73],"long":[74],"short-term":[75,136],"memory":[76],"methods":[77],"(LSTMs)":[78],"applied":[80],"mine":[82],"temporal":[84],"closeness":[85],"period":[87],"properties;":[88],"(3)":[89],"external":[90,109],"factors":[91,110],"such":[92],"as":[93],"diffusion,":[95],"time":[96],"characteristics":[97],"also":[99],"considered":[100],"enhance":[102],"performance;":[104],"(4)":[105],"CNN,":[106],"LSTMs":[107],"integrated":[112],"into":[113],"final":[115],"CNN-LSTM":[116],"based":[117],"Experiment":[120],"results":[121],"on":[122],"public":[124],"dataset":[125],"indicate":[126],"that":[127],"consideration":[129],"advantage":[134],"in":[135],"prediction.":[138]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3026663574","counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-03-20T22:20:17.434748","created_date":"2020-05-29"}