{"id":"https://openalex.org/W3126441351","doi":"https://doi.org/10.1109/tii.2021.3055283","title":"FASTGNN: A Topological Information Protected Federated Learning Approach for Traffic Speed Forecasting","display_name":"FASTGNN: A Topological Information Protected Federated Learning Approach for Traffic Speed Forecasting","publication_year":2021,"publication_date":"2021-01-29","ids":{"openalex":"https://openalex.org/W3126441351","doi":"https://doi.org/10.1109/tii.2021.3055283","mag":"3126441351"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2021.3055283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3055283","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Industrial Informatics","raw_type":"journal-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/A5061304518","display_name":"Chenhan Zhang","orcid":"https://orcid.org/0000-0002-2352-0485"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["AU","CN"],"is_corresponding":true,"raw_author_name":"Chenhan Zhang","raw_affiliation_strings":["Department of Computer Science and Engineering, Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen, China","University of Technology Sydney, Ultimo, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]},{"raw_affiliation_string":"University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100634778","display_name":"Shuyu Zhang","orcid":"https://orcid.org/0000-0002-0291-7651"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyu Zhang","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076130415","display_name":"James J. Q. Yu","orcid":"https://orcid.org/0000-0002-6392-6711"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"James J. Q. Yu","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005228053","display_name":"Shui Yu","orcid":"https://orcid.org/0000-0003-4485-6743"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shui Yu","raw_affiliation_strings":["School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061304518"],"corresponding_institution_ids":["https://openalex.org/I114017466","https://openalex.org/I3045169105"],"apc_list":null,"apc_paid":null,"fwci":15.5406,"has_fulltext":false,"cited_by_count":178,"citation_normalized_percentile":{"value":0.99682643,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"17","issue":"12","first_page":"8464","last_page":"8474"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.995199978351593,"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":0.7931571006774902},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.5820347666740417},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5724328756332397},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5365676283836365},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.5286926031112671},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4678512215614319},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4657614529132843},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4134524166584015},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39108067750930786},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36521369218826294},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2615774869918823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7931571006774902},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.5820347666740417},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5724328756332397},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5365676283836365},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.5286926031112671},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4678512215614319},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4657614529132843},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4134524166584015},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39108067750930786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36521369218826294},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2615774869918823},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical 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/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tii.2021.3055283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3055283","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Industrial Informatics","raw_type":"journal-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/148481","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/148481","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1896743484","https://openalex.org/W1966836595","https://openalex.org/W2027595342","https://openalex.org/W2045390367","https://openalex.org/W2108196201","https://openalex.org/W2346653774","https://openalex.org/W2398137098","https://openalex.org/W2541884796","https://openalex.org/W2579495707","https://openalex.org/W2613331518","https://openalex.org/W2756203131","https://openalex.org/W2788134583","https://openalex.org/W2793423901","https://openalex.org/W2883059862","https://openalex.org/W2884128153","https://openalex.org/W2902252938","https://openalex.org/W2906257585","https://openalex.org/W2912213068","https://openalex.org/W2935726879","https://openalex.org/W2941717697","https://openalex.org/W2963124587","https://openalex.org/W2963358464","https://openalex.org/W2963858333","https://openalex.org/W2965341826","https://openalex.org/W2965399951","https://openalex.org/W2974087501","https://openalex.org/W2974175488","https://openalex.org/W2989567700","https://openalex.org/W3010852232","https://openalex.org/W3011892127","https://openalex.org/W3015712039","https://openalex.org/W3016632787","https://openalex.org/W3045736930","https://openalex.org/W3049535205","https://openalex.org/W3086579950","https://openalex.org/W3090615085","https://openalex.org/W3101220048","https://openalex.org/W3103720336","https://openalex.org/W3112885687","https://openalex.org/W3125796803","https://openalex.org/W4205228770","https://openalex.org/W4297733535","https://openalex.org/W4318619660","https://openalex.org/W6639635377","https://openalex.org/W6728757088","https://openalex.org/W6746015598","https://openalex.org/W6748555476","https://openalex.org/W6782070294"],"related_works":["https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2734500670","https://openalex.org/W2558166297","https://openalex.org/W2315671126","https://openalex.org/W798507144","https://openalex.org/W2964481303","https://openalex.org/W2571704763","https://openalex.org/W1751413323","https://openalex.org/W1896743484"],"abstract_inverted_index":{"Federated":[0],"learning":[1,43,78,144],"has":[2],"been":[3],"applied":[4],"to":[5,12,44,80,107,112],"various":[6],"tasks":[7,47],"in":[8,26],"intelligent":[9,27],"transportation":[10,28,68],"systems":[11,29],"protect":[13,56],"data":[14,58],"privacy":[15,170],"through":[16],"decentralized":[17],"training":[18,120],"schemes.":[19],"The":[20],"majority":[21],"of":[22,64,67],"the":[23,45,51,57,62,96,114,141,169],"state-of-the-art":[24],"models":[25,111],"(ITS)":[30],"are":[31],"graph":[32,131],"neural":[33,132],"networks":[34,133],"(GNN)-based":[35],"for":[36,94,117,135,150],"spatial":[37],"information":[38,66],"learning.":[39],"When":[40],"applying":[41],"federated":[42,77,143],"ITS":[46],"with":[48],"GNN-based":[49,110,126],"models,":[50],"existing":[52],"frameworks":[53],"can":[54,164],"only":[55],"privacy;":[59],"however,":[60],"ignore":[61],"one":[63],"topological":[65,97],"networks.":[69],"In":[70],"this":[71,82],"article,":[72],"we":[73,85,123],"propose":[74,101,124],"a":[75,87,118,125,158],"novel":[76],"framework":[79,145],"tackle":[81],"problem.":[83],"Specifically,":[84],"introduce":[86],"differential":[88],"privacy-based":[89],"adjacency":[90,103],"matrix":[91,104],"preserving":[92],"approach":[93,106],"protecting":[95],"information.":[98],"We":[99,139],"also":[100],"an":[102],"aggregation":[105],"allow":[108],"local":[109],"access":[113],"global":[115],"network":[116],"better":[119],"effect.":[121],"Furthermore,":[122],"model":[127],"named":[128],"attention-based":[129],"spatial-temporal":[130],"(ASTGNN)":[134],"traffic":[136,151],"speed":[137,152],"forecasting.":[138,153],"integrate":[140],"proposed":[142],"and":[146],"ASTGNN":[147],"as":[148],"FASTGNN":[149,163],"Extensive":[154],"case":[155],"studies":[156],"on":[157],"real-world":[159],"dataset":[160],"demonstrate":[161],"that":[162],"develop":[165],"accurate":[166],"forecasting":[167],"under":[168],"preservation":[171],"constraint.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":43},{"year":2024,"cited_by_count":56},{"year":2023,"cited_by_count":37},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":9}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
