{"id":"https://openalex.org/W4321636790","doi":"https://doi.org/10.1109/wcsp55476.2022.10039323","title":"Federated Spatio-Temporal Traffic Flow Prediction Based on Graph Convolutional Network","display_name":"Federated Spatio-Temporal Traffic Flow Prediction Based on Graph Convolutional Network","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4321636790","doi":"https://doi.org/10.1109/wcsp55476.2022.10039323"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp55476.2022.10039323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp55476.2022.10039323","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5083415358","display_name":"Hanqiu Wang","orcid":"https://orcid.org/0000-0003-2852-4028"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hanqiu Wang","raw_affiliation_strings":["School of Software Engineering, Tongji University,Shanghai,China","School of Software Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University,Shanghai,China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100695813","display_name":"Rongqing Zhang","orcid":"https://orcid.org/0000-0003-3774-6247"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongqing Zhang","raw_affiliation_strings":["School of Software Engineering, Tongji University,Shanghai,China","School of Software Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University,Shanghai,China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068110218","display_name":"Xiang Cheng","orcid":"https://orcid.org/0000-0002-5943-0326"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Cheng","raw_affiliation_strings":["School of Electronics, Peking University,Beijing,China","School of Electronics, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics, Peking University,Beijing,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Electronics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089217677","display_name":"Liuqing Yang","orcid":"https://orcid.org/0009-0003-1239-5804"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Liuqing Yang","raw_affiliation_strings":["IoT Thrust &#x0026; INTR Thrust, The Hong Kong University of Science and Technology (GZ),Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"IoT Thrust &#x0026; INTR Thrust, The Hong Kong University of Science and Technology (GZ),Guangzhou,China","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083415358"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":1.4817,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.80005431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"221","last_page":"225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9790999889373779,"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":0.9318000078201294,"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":0.8565142750740051},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5954050421714783},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5578262209892273},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.4992103576660156},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4906224310398102},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.44809889793395996},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.422201931476593},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.41191089153289795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40222954750061035},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20555275678634644},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.19869932532310486},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.17232534289360046}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8565142750740051},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5954050421714783},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5578262209892273},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.4992103576660156},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4906224310398102},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.44809889793395996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.422201931476593},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.41191089153289795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40222954750061035},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20555275678634644},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.19869932532310486},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.17232534289360046},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wcsp55476.2022.10039323","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp55476.2022.10039323","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-126611","is_oa":false,"landing_page_url":"http://www.scopus.com/record/display.url?eid=2-s2.0-85149128781&origin=inward","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2014663916","display_name":null,"funder_award_id":"2021ZD0112700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4925971499","display_name":null,"funder_award_id":"61901302,62271351,62125101","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G8307752930","display_name":null,"funder_award_id":"20ZR1462400","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320327025","display_name":"State Key Laboratory of Advanced Optical Communication Systems and Networks","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2108196201","https://openalex.org/W2528639018","https://openalex.org/W2756203131","https://openalex.org/W2902765948","https://openalex.org/W2903871660","https://openalex.org/W2963440544","https://openalex.org/W2974175488","https://openalex.org/W3010852232","https://openalex.org/W3086579950","https://openalex.org/W3101220048","https://openalex.org/W3103720336","https://openalex.org/W3126441351","https://openalex.org/W4213090353","https://openalex.org/W6728757088"],"related_works":["https://openalex.org/W2793666424","https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W1521063997","https://openalex.org/W2362101859","https://openalex.org/W2791431590","https://openalex.org/W1978900583","https://openalex.org/W2350688482","https://openalex.org/W2053575972","https://openalex.org/W4323256314"],"abstract_inverted_index":{"In":[0,97,127,141],"recent":[1],"years,":[2],"traffic":[3,21,77,106,183],"flow":[4,22,107],"prediction":[5,23,108,184],"has":[6],"attracted":[7],"increasing":[8],"interest":[9],"from":[10,49],"both":[11,118],"academia":[12],"and":[13,15,52,121,155],"industry,":[14],"existing":[16],"data-driven":[17],"learning":[18,95,134],"models":[19],"for":[20,36,151],"have":[24],"achieved":[25],"excellent":[26],"success.":[27],"However,":[28],"this":[29,88,98],"requires":[30],"a":[31,92,102,148],"large":[32],"number":[33,69],"of":[34,70,124,170],"datasets":[35,177],"efficient":[37],"model":[38,109,171,185],"training,":[39],"while":[40,79,198],"it":[41],"is":[42,82],"difficult":[43],"to":[44,73,162],"acquire":[45],"all":[46],"the":[47,65,68,142,164,168],"data":[48,54],"one":[50],"agent,":[51],"thus":[53],"collaboration":[55],"among":[56],"different":[57],"agents":[58],"becomes":[59],"an":[60,83,131,157],"attracting":[61],"trend.":[62],"Moreover,":[63],"with":[64,136],"increase":[66],"in":[67],"agents,":[71],"how":[72],"perform":[74],"accurate":[75],"multi-agent":[76],"forecasting":[78],"protecting":[80],"privacy":[81],"important":[84],"issue.":[85],"To":[86],"address":[87],"challenge,":[89],"we":[90,100,129,146],"introduce":[91],"privacy-preserving":[93],"federated":[94,133],"framework.":[96],"paper,":[99],"propose":[101],"novel":[103],"Dynamic":[104],"Spatio-Temporal":[105],"based":[110,174],"on":[111,175],"graph":[112],"convolutional":[113],"network":[114],"(DST-GCN),":[115],"which":[116],"incorporates":[117],"dynamic":[119],"spatial":[120],"temporal":[122],"dependence":[123],"intersection":[125],"traffic.":[126],"addition,":[128],"provide":[130],"improved":[132],"framework":[135],"opportunistic":[137],"client":[138,159],"selection":[139,160],"(FLoS).":[140],"proposed":[143,181,192],"FLoS":[144,193],"protocol,":[145],"employ":[147],"FedAVG":[149],"algorithm":[150,161],"secure":[152],"parameter":[153],"aggregation":[154],"design":[156],"optimal":[158],"reduce":[163],"communication":[165,200],"overhead":[166],"during":[167],"transfer":[169],"updates.":[172],"Experiments":[173],"real-world":[176],"demonstrate":[178],"that":[179],"our":[180,191],"DST-GCN":[182],"outperforms":[186],"state-of-the-art":[187],"baseline":[188],"models.":[189],"And":[190],"can":[194],"achieve":[195],"superior":[196],"results":[197],"reducing":[199],"consumption.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2}],"updated_date":"2026-02-26T08:16:20.718346","created_date":"2025-10-10T00:00:00"}
