{"id":"https://openalex.org/W2976712891","doi":"https://doi.org/10.1109/iccse.2019.8845432","title":"Short-Term Traffic Flow Prediction and Its Application Based on the Basis-Prediction Model and Local Weighted Partial Least Squares Method","display_name":"Short-Term Traffic Flow Prediction and Its Application Based on the Basis-Prediction Model and Local Weighted Partial Least Squares Method","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2976712891","doi":"https://doi.org/10.1109/iccse.2019.8845432","mag":"2976712891"},"language":"en","primary_location":{"id":"doi:10.1109/iccse.2019.8845432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse.2019.8845432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th International Conference on Computer Science &amp; Education (ICCSE)","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/A5074083547","display_name":"Zhiyang Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyang Gu","raw_affiliation_strings":["Department of Automation, Xiamen University, Xiamen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008406595","display_name":"Zhou Sun","orcid":"https://orcid.org/0000-0003-0788-0955"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sun Zhou","raw_affiliation_strings":["Department of Automation, Xiamen University, Xiamen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3251,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64277611,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"22","issue":null,"first_page":"992","last_page":"997"},"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":0.994700014591217,"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"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9839000105857849,"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/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6565154790878296},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.6152745485305786},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5862448215484619},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.5634511709213257},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5629223585128784},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5124018788337708},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4913605749607086},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.48440033197402954},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39844873547554016},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2905430793762207},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2616875171661377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14714863896369934}],"concepts":[{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6565154790878296},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.6152745485305786},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5862448215484619},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5634511709213257},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5629223585128784},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5124018788337708},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4913605749607086},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.48440033197402954},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39844873547554016},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2905430793762207},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2616875171661377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14714863896369934},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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":1,"locations":[{"id":"doi:10.1109/iccse.2019.8845432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse.2019.8845432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th International Conference on Computer Science &amp; Education (ICCSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1776391967","https://openalex.org/W1779974200","https://openalex.org/W1984009504","https://openalex.org/W2040002190","https://openalex.org/W2156792979","https://openalex.org/W2344029946","https://openalex.org/W2751760169","https://openalex.org/W6638232476"],"related_works":["https://openalex.org/W3034924094","https://openalex.org/W3094954546","https://openalex.org/W1488708774","https://openalex.org/W1982811510","https://openalex.org/W4391100477","https://openalex.org/W2402189625","https://openalex.org/W4327779705","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,18,33,43,54,73,153,185],"forecasting":[2],"is":[3,129,139],"one":[4],"of":[5,16,40,61,70,116,144,151,154,165,176,182],"the":[6,38,67,71,80,86,100,107,117,133,137,142,145,166,174,180],"key":[7],"issues":[8],"in":[9,85],"smart":[10],"traffic":[11,17,32,42,53,72,119,147,152,184],"systems.":[12],"The":[13,88,103,121,170],"changing":[14,68],"process":[15],"involves":[19],"high":[20],"randomness,":[21],"environmental":[22],"interference":[23,82],"and":[24,74,95,106,136,161],"measurement":[25],"noise,":[26],"which":[27,78],"bring":[28],"difficulties":[29],"to":[30,131],"accurate":[31],"prediction.":[34],"Aiming":[35],"at":[36],"improving":[37],"accuracy":[39,181],"short-term":[41,183],"prediction,":[44],"this":[45],"paper":[46],"presents":[47],"a":[48,62,75],"basis-prediction":[49,168],"model.":[50,169],"A":[51],"raw":[52,118,146],"series":[55,64,77,90,105,109,135],"can":[56,110],"be":[57,111],"deemed":[58],"as":[59,141],"summation":[60],"basis":[63,89,104,134],"that":[65,173,177],"implies":[66],"trend":[69],"deviation":[76,101,108],"represents":[79],"random":[81],"information":[83],"involved":[84],"flow.":[87,120,148],"mainly":[91],"comprises":[92],"low-frequency":[93],"signals":[94],"some":[96],"high-frequency":[97],"ones":[98],"compose":[99],"series.":[102],"obtained":[112],"using":[113],"wavelet":[114],"decomposition":[115],"local":[122],"weighted":[123],"partial":[124],"least":[125],"squares":[126],"(LW-PLS)":[127],"method":[128],"adopted":[130],"predict":[132],"result":[138],"used":[140,162],"prediction":[143,186],"Real":[149],"data":[150],"Xinbei":[155],"city,":[156],"Taiwan":[157],"province":[158],"was":[159],"collected":[160],"for":[163],"validation":[164],"proposed":[167],"results":[171],"show":[172],"use":[175],"model":[178],"improves":[179],"by":[187],"about":[188],"2%":[189],"on":[190],"average.":[191]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
