{"id":"https://openalex.org/W4312729960","doi":"https://doi.org/10.1145/3565291.3565299","title":"Spatio-Temporal Correlation Augmented Model for Traffic Flow Prediction in Urban Areas","display_name":"Spatio-Temporal Correlation Augmented Model for Traffic Flow Prediction in Urban Areas","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4312729960","doi":"https://doi.org/10.1145/3565291.3565299"},"language":"en","primary_location":{"id":"doi:10.1145/3565291.3565299","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565291.3565299","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data Technologies","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/A5100646919","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0002-9822-6782"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yue Wang","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, China"],"raw_orcid":"https://orcid.org/0000-0002-9822-6782","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423307","display_name":"Ming Chen","orcid":"https://orcid.org/0000-0003-2797-5564"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Chen","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, China"],"raw_orcid":"https://orcid.org/0000-0003-2797-5564","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077224988","display_name":"Aite Zhao","orcid":"https://orcid.org/0000-0003-3494-175X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aite Zhao","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, China"],"raw_orcid":"https://orcid.org/0000-0003-3494-175X","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100646919"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.108,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44710722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"48","last_page":"53"},"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":0.9926000237464905,"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":0.9897000193595886,"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/computer-science","display_name":"Computer science","score":0.7422662973403931},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6914692521095276},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6841554045677185},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5945073366165161},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5298538208007812},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4552832841873169},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.4122958183288574},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3761819303035736},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11489927768707275}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7422662973403931},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6914692521095276},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6841554045677185},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5945073366165161},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5298538208007812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4552832841873169},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.4122958183288574},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3761819303035736},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11489927768707275},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3565291.3565299","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3565291.3565299","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Big Data Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2618668243","display_name":null,"funder_award_id":"62106117","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1789808336","https://openalex.org/W2064675550","https://openalex.org/W2531563875","https://openalex.org/W2612472936","https://openalex.org/W2743500757","https://openalex.org/W2800806089","https://openalex.org/W2898113880","https://openalex.org/W2901504064","https://openalex.org/W2903266766","https://openalex.org/W2921532413","https://openalex.org/W2947314437","https://openalex.org/W2950635152","https://openalex.org/W2952871130","https://openalex.org/W2962790412","https://openalex.org/W2999301586","https://openalex.org/W3033688252","https://openalex.org/W3039628929","https://openalex.org/W3045219832","https://openalex.org/W3045306463","https://openalex.org/W3049596687","https://openalex.org/W3092713078","https://openalex.org/W3102272367","https://openalex.org/W3116782049","https://openalex.org/W3161236498","https://openalex.org/W3175286348","https://openalex.org/W3176186894","https://openalex.org/W3182305291","https://openalex.org/W3194218357","https://openalex.org/W3198637603","https://openalex.org/W3215509581","https://openalex.org/W4205454839","https://openalex.org/W4205996475","https://openalex.org/W4226288807","https://openalex.org/W4245406319","https://openalex.org/W4283167368","https://openalex.org/W4285288510","https://openalex.org/W6966669703"],"related_works":["https://openalex.org/W2587362999","https://openalex.org/W432084041","https://openalex.org/W2963251637","https://openalex.org/W2986732134","https://openalex.org/W2394010358","https://openalex.org/W2361078351","https://openalex.org/W2052374615","https://openalex.org/W4239349137","https://openalex.org/W1463884142","https://openalex.org/W239469043"],"abstract_inverted_index":{"As":[0],"an":[1],"important":[2],"component":[3],"of":[4,92],"modern":[5],"intelligent":[6],"traffic":[7,10,19,29,39,60,73,93],"management":[8],"systems,":[9],"forecasting":[11],"can":[12],"provide":[13],"effective":[14],"technical":[15],"support":[16],"for":[17,28,72],"highway":[18],"control":[20],"and":[21,41,46],"scheduling.":[22],"However,":[23],"existing":[24],"temporal":[25],"convolutional":[26],"networks":[27],"flow":[30,61,74,94],"prediction":[31,62,75],"have":[32],"limited":[33],"perceptual":[34],"fields,":[35],"cannot":[36],"capture":[37],"long-term":[38],"correlation,":[40],"few":[42],"works":[43],"integrate":[44],"complex":[45,55],"variable":[47],"external":[48],"factors.":[49],"To":[50],"fully":[51],"exploit":[52],"the":[53,90],"global":[54],"spatio-temporal":[56,67],"correlation":[57,68],"to":[58],"improve":[59],"accuracy,":[63],"we":[64],"propose":[65],"a":[66],"augmented":[69],"model":[70],"(STCA)":[71],"in":[76],"urban":[77],"areas.":[78],"Extensive":[79],"experiments":[80],"on":[81],"two":[82],"real-world":[83],"datasets":[84],"show":[85],"that":[86],"our":[87],"method":[88],"improves":[89],"accuracy":[91],"prediction.":[95]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
