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Fourier Graph Convolution Network for Time Series Prediction

dc.contributor.authorLiao, Lyuchao
dc.contributor.authorHu, Zhiyuan
dc.contributor.authorHsu, Chih-Yu
dc.contributor.authorSu, Jinya
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Machine Learningen
dc.date.accessioned2023-07-04T13:59:01Z
dc.date.available2023-07-04T13:59:01Z
dc.date.issued2023-03-29
dc.descriptionThis work was supported in part by the projects of the National Natural Science Foundation of China (41971340, 61304199), projects of Fujian Provincial Department of Science and Technology (2021Y4019, 2020D002, 2020L3014, 2019I0019, 2008Y3001), projects of Fujian Provincial Department of Finance (GY-Z230007), and the project of Fujian Provincial Universities Engineering Research Center for Intelligent Driving Technology (Fujian University of Technology) (KF-J21012).en
dc.description.statusPeer revieweden
dc.format.extent4728774
dc.identifier235428055
dc.identifierb26d92c1-65f7-4713-a682-382972804f59
dc.identifier85152793503
dc.identifier.citationLiao, L, Hu, Z, Hsu, C-Y & Su, J 2023, 'Fourier Graph Convolution Network for Time Series Prediction', Mathematics, vol. 11, no. 7, 1649. https://doi.org/10.3390/math11071649en
dc.identifier.doi10.3390/math11071649
dc.identifier.iss7en
dc.identifier.issn2227-7390
dc.identifier.urihttps://hdl.handle.net/2164/21100
dc.identifier.vol11en
dc.language.isoeng
dc.relation.ispartofMathematicsen
dc.subjecttraffic flow predictionen
dc.subjectperiodicityen
dc.subjectvolatilityen
dc.subjectFourier embeddingen
dc.subjectspatial-temporal ChebyNeten
dc.subjectgraph convolutional neural networken
dc.subjectQA Mathematicsen
dc.subject.lccQAen
dc.titleFourier Graph Convolution Network for Time Series Predictionen
dc.typeJournal articleen

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