{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,13]],"date-time":"2026-11-13T01:41:37Z","timestamp":1794534097822,"version":"4.9.1"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972069"],"award-info":[{"award-number":["61972069"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61836007"],"award-info":[{"award-number":["61836007"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61832017"],"award-info":[{"award-number":["61832017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62272086"],"award-info":[{"award-number":["62272086"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Municipal Science and Technology R&D Funding Basic Research Program","award":["JCYJ20210324133607021"],"award-info":[{"award-number":["JCYJ20210324133607021"]}]},{"name":"Municipal Government of Quzhou","award":["2022D037"],"award-info":[{"award-number":["2022D037"]}]},{"name":"Key Laboratory of Data Intelligence and Cognitive Computing"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1109\/tkde.2023.3324501","type":"journal-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T18:08:10Z","timestamp":1697566090000},"page":"2671-2685","source":"Crossref","is-referenced-by-count":60,"title":["STWave+: A Multi-Scale Efficient Spectral Graph Attention Network With Long-Term Trends for Disentangled Traffic Flow Forecasting"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6797-7292","authenticated-orcid":false,"given":"Yuchen","family":"Fang","sequence":"first","affiliation":[{"name":"Yangtze Delta Region Institute (Quzhou), School of Computer Science and Engineering, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5011-8697","authenticated-orcid":false,"given":"Yanjun","family":"Qin","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6827-4225","authenticated-orcid":false,"given":"Haiyong","family":"Luo","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4784-5778","authenticated-orcid":false,"given":"Fang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0217-3998","authenticated-orcid":false,"given":"Kai","family":"Zheng","sequence":"additional","affiliation":[{"name":"Yangtze Delta Region Institute (Quzhou), School of Computer Science and Engineering, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00153"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2018.00058"},{"key":"ref3","first-page":"1","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16542"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467430"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3197640"},{"key":"ref8","first-page":"1","article-title":"CoST: Contrastive learning of disentangled seasonal-trend representations for time series forecasting","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Woo"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/264"},{"key":"ref10","first-page":"17804","article-title":"Adaptive graph convolutional recurrent network for traffic forecasting","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Bai"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411941"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/326"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411940"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5477"},{"key":"ref15","first-page":"28877","article-title":"Do transformers really perform badly for graph representation?","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Ying"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3149815"},{"key":"ref17","article-title":"Graph wavelet neural network","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xu"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE55515.2023.00046"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16088"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.2307\/j.ctv14jx6sm"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3837\/tiis.2016.01.008"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1061\/(asce)0733-947x(2003)129:6(664)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2004.837813"},{"issue":"1","key":"ref24","first-page":"22","article-title":"Short-term traffic and travel time prediction models","volume":"22","author":"Van Lint","year":"2012","journal-title":"Artif. Intell. Appl. to Crit. Transp. Issues"},{"key":"ref25","first-page":"1725","article-title":"Simple and deep graph convolutional networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557540"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2012.2225049"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2950327"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s11269-019-02273-0"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3564753"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.102620"},{"key":"ref33","article-title":"Adaptive graph convolution networks for traffic flow forecasting","author":"Li","year":"2023"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"issue":"1","key":"ref35","first-page":"2744","article-title":"Multivariate bayesian structural time series model","volume":"19","author":"Qiu","year":"2018","journal-title":"J. Mach. Learn. Res."},{"key":"ref36","volume-title":"Elements of Causal Inference: Foundations and Learning Algorithms","author":"Peters","year":"2017"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1063\/1.4823127"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref39","article-title":"A generalization of transformer networks to graphs","author":"Dwivedi","year":"2020"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2010.04.005"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3213589"},{"key":"ref42","first-page":"5812","article-title":"Graph contrastive learning with augmentations","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"You"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1137\/1.9780898719628"},{"key":"ref44","first-page":"435","article-title":"Deep stacked residual neural network and bidirectional LSTM for speed prediction on real-life traffic data","volume-title":"Proc. Eur. Conf. Artif. Intell.","author":"Elmi"},{"key":"ref45","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Sutskever"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5438"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/10506969\/10286992.pdf?arnumber=10286992","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T22:25:40Z","timestamp":1715120740000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10286992\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6]]},"references-count":46,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2023.3324501","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6]]}}}