{"id":"https://openalex.org/W2899617249","doi":"https://doi.org/10.1109/access.2018.2879055","title":"Short-Term Traffic Flow Forecasting by Selecting Appropriate Predictions Based on Pattern Matching","display_name":"Short-Term Traffic Flow Forecasting by Selecting Appropriate Predictions Based on Pattern Matching","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2899617249","doi":"https://doi.org/10.1109/access.2018.2879055","mag":"2899617249"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2879055","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2879055","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2879055","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024477428","display_name":"Dongfang Ma","orcid":"https://orcid.org/0000-0002-9334-1570"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongfang Ma","raw_affiliation_strings":["Institute of Marine Sensing and Networking, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9334-1570","affiliations":[{"raw_affiliation_string":"Institute of Marine Sensing and Networking, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083934948","display_name":"Bowen Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Sheng","raw_affiliation_strings":["Institute of Marine Sensing and Networking, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Marine Sensing and Networking, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101960327","display_name":"Sheng Jin","orcid":"https://orcid.org/0000-0001-6110-0783"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Jin","raw_affiliation_strings":["Institute of Intelligent Transportation Systems, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6110-0783","affiliations":[{"raw_affiliation_string":"Institute of Intelligent Transportation Systems, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101507446","display_name":"Xiaolong Ma","orcid":"https://orcid.org/0000-0002-6842-7591"},"institutions":[{"id":"https://openalex.org/I4210111795","display_name":"Hisense (China)","ror":"https://ror.org/0276vcd78","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210111795"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Ma","raw_affiliation_strings":["Research and Development Center, Qingdao Hisense TransTech Co., Ltd., Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research and Development Center, Qingdao Hisense TransTech Co., Ltd., Qingdao, China","institution_ids":["https://openalex.org/I4210111795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077795850","display_name":"Peng Gao","orcid":"https://orcid.org/0000-0002-6719-7683"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]},{"id":"https://openalex.org/I4210119987","display_name":"Qingdao Municipal Hospital","ror":"https://ror.org/02jqapy19","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210119987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Gao","raw_affiliation_strings":["Transportation Public Information Service Center, Qingdao Municipal Commission of Transport, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Transportation Public Information Service Center, Qingdao Municipal Commission of Transport, Qingdao, China","institution_ids":["https://openalex.org/I108688024","https://openalex.org/I4210119987"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.1102,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.93453853,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"75629","last_page":"75638"},"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":0.9983999729156494,"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":0.995199978351593,"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":0.7497100830078125},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6200252771377563},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5715311765670776},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5667900443077087},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5595866441726685},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5469586253166199},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5389474630355835},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4974711239337921},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4633626639842987},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41231152415275574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40102696418762207},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1496240496635437},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09641733765602112}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7497100830078125},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6200252771377563},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5715311765670776},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5667900443077087},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5595866441726685},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5469586253166199},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5389474630355835},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4974711239337921},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4633626639842987},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41231152415275574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40102696418762207},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1496240496635437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09641733765602112},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2879055","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2879055","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:eabe6939ad584df6a650d0975224821f","is_oa":true,"landing_page_url":"https://doaj.org/article/eabe6939ad584df6a650d0975224821f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 75629-75638 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2879055","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2879055","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1856576220","display_name":"\u4eba\u5de5\u667a\u80fd\u9a71\u52a8\u7684\u57ce\u5e02\u4ea4\u901a\u63a7\u5236\u7406\u8bba\u4e0e\u65b9\u6cd5","funder_award_id":"LR19F030002","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G213062781","display_name":null,"funder_award_id":"91746105","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3112677441","display_name":null,"funder_award_id":"2018QNA050","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6143760251","display_name":null,"funder_award_id":"2018QNA4035","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7048732114","display_name":null,"funder_award_id":"LY17F030009","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G7370932115","display_name":null,"funder_award_id":"61773338","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8237307337","display_name":null,"funder_award_id":"61773337","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W252542266","https://openalex.org/W793439335","https://openalex.org/W1485009520","https://openalex.org/W1544613517","https://openalex.org/W1594839485","https://openalex.org/W1875626450","https://openalex.org/W1909275259","https://openalex.org/W1982606801","https://openalex.org/W1987916558","https://openalex.org/W1996820377","https://openalex.org/W2003766622","https://openalex.org/W2004353783","https://openalex.org/W2013050169","https://openalex.org/W2013131147","https://openalex.org/W2018569350","https://openalex.org/W2021914902","https://openalex.org/W2024558842","https://openalex.org/W2027392238","https://openalex.org/W2028507901","https://openalex.org/W2032057266","https://openalex.org/W2036785686","https://openalex.org/W2052429958","https://openalex.org/W2061062671","https://openalex.org/W2061358509","https://openalex.org/W2067680836","https://openalex.org/W2093134417","https://openalex.org/W2108196201","https://openalex.org/W2109204689","https://openalex.org/W2109563136","https://openalex.org/W2119436991","https://openalex.org/W2137214660","https://openalex.org/W2139606794","https://openalex.org/W2156793027","https://openalex.org/W2158107760","https://openalex.org/W2165137963","https://openalex.org/W2165991108","https://openalex.org/W2217607432","https://openalex.org/W2288572574","https://openalex.org/W2463827188","https://openalex.org/W2464799525","https://openalex.org/W2531473348","https://openalex.org/W2563118655","https://openalex.org/W2570946799","https://openalex.org/W2573587735","https://openalex.org/W2588847126","https://openalex.org/W2592437429","https://openalex.org/W2599552708","https://openalex.org/W2610635404","https://openalex.org/W2626290941","https://openalex.org/W2737904742","https://openalex.org/W2743812350","https://openalex.org/W2751015792","https://openalex.org/W2756203131","https://openalex.org/W2767563563","https://openalex.org/W2768727525","https://openalex.org/W2775717462","https://openalex.org/W2776922538","https://openalex.org/W2782143633","https://openalex.org/W2808448224","https://openalex.org/W2808871417","https://openalex.org/W2808990700","https://openalex.org/W2809951001","https://openalex.org/W2888727839","https://openalex.org/W2891363375","https://openalex.org/W2891720564","https://openalex.org/W3103720336","https://openalex.org/W3134617058","https://openalex.org/W6628877408","https://openalex.org/W6659849045","https://openalex.org/W6728411086","https://openalex.org/W6730654704","https://openalex.org/W6791657429"],"related_works":["https://openalex.org/W2804364458","https://openalex.org/W42295635","https://openalex.org/W1973996291","https://openalex.org/W4298130764","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2330575325","https://openalex.org/W2090259340","https://openalex.org/W4388747848","https://openalex.org/W2393816671"],"abstract_inverted_index":{"Forecasting":[0],"short-term":[1],"traffic":[2,9,42],"flow":[3,43],"is":[4,67,82,111,126],"one":[5],"critical":[6],"component":[7],"in":[8,161,166],"management":[10],"to":[11,33,73,128],"improve":[12,147],"operational":[13],"efficiency.":[14],"Data":[15],"driven":[16],"method,":[17,54],"which":[18,38],"trains":[19],"the":[20,80,100,105,114,118,121,148,157],"predictor":[21,81,115,144],"with":[22],"historical":[23,65],"data":[24,66],"across":[25],"a":[26,89,133],"given":[27],"past":[28],"period,":[29],"have":[30],"been":[31],"proved":[32],"perform":[34],"well.":[35],"However,":[36],"days":[37],"experience":[39],"significantly":[40,146],"different":[41],"patterns,":[44,75],"negatively":[45],"influence":[46],"forecasting":[47],"results.":[48],"This":[49],"paper":[50],"proposes":[51],"an":[52,142],"advanced":[53],"making":[55],"use":[56],"of":[57,102,124,150,168],"appropriate":[58,143],"prediction":[59,169],"based":[60,87],"on":[61,88,132],"pattern":[62],"matching.":[63],"First,":[64],"divided":[68],"into":[69],"several":[70],"groups,":[71],"according":[72],"their":[74],"by":[76,117],"clustering":[77],"algorithms.":[78],"Then":[79],"trained":[83,116],"for":[84],"each":[85,97,109],"group":[86,110,119],"convolutional":[90],"neural":[91],"networks":[92],"and":[93,108,113,171],"long-short-term-memory":[94],"model.":[95],"For":[96],"time":[98],"point,":[99],"degree":[101,123],"similarity":[103,125],"between":[104],"target":[106],"day":[107],"measured,":[112],"possessing":[120],"highest":[122],"selected":[127],"be":[129],"appropriate.":[130],"Based":[131],"case":[134],"study":[135],"from":[136],"Seattle,":[137],"we":[138,154],"show":[139],"that":[140,156],"selecting":[141],"can":[145],"accuracy":[149,170],"predictions.":[151],"In":[152],"addition,":[153],"demonstrate":[155],"new":[158],"method":[159],"can,":[160],"general,":[162],"outperform":[163],"alternative":[164],"methods":[165],"terms":[167],"stability.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":4}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-10-10T00:00:00"}