{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T22:21:13Z","timestamp":1774650073870,"version":"3.50.1"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"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":["62102041"],"award-info":[{"award-number":["62102041"]}],"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":["61876023"],"award-info":[{"award-number":["61876023"]}],"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":["61902035"],"award-info":[{"award-number":["61902035"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1109\/tits.2022.3167019","type":"journal-article","created":{"date-parts":[[2022,5,13]],"date-time":"2022-05-13T19:29:50Z","timestamp":1652470190000},"page":"19201-19212","source":"Crossref","is-referenced-by-count":79,"title":["ESTNet: Embedded Spatial-Temporal Network for Modeling Traffic Flow Dynamics"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1912-8536","authenticated-orcid":false,"given":"Guiyang","family":"Luo","sequence":"first","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"given":"Hui","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2552-333X","authenticated-orcid":false,"given":"Quan","family":"Yuan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6720-9533","authenticated-orcid":false,"given":"Jinglin","family":"Li","sequence":"additional","affiliation":[{"name":"Science and Technology on Communication Networks Laboratory, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9185-3989","authenticated-orcid":false,"given":"Fei-Yue","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CC.2018.8424578"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2019.2953163"},{"key":"ref3","article-title":"Deep learning on traffic prediction: Methods, analysis and future directions","author":"Yin","year":"2020","journal-title":"arXiv:2004.08555"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5477"},{"key":"ref5","first-page":"1","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Li"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313577"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2020.2999617"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.3025491"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3115823"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.013.2100087"},{"key":"ref11","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Shi"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10735"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/264"},{"key":"ref14","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kipf"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5470"},{"key":"ref16","first-page":"1","article-title":"Adaptive graph convolutional recurrent network for traffic forecasting","volume-title":"Proc. NIPS","volume":"33","author":"Bai"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403127"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5438"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/262"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2866435"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2947806"},{"issue":"8","key":"ref22","first-page":"1289","article-title":"Advances and perspectives on applications of deep learning in visual object detection","volume":"43","author":"Zhang","year":"2017","journal-title":"Acta Automatica Sinica"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2996245"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317872"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/WCSP.2017.8171119"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2909904"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2018.2791505"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015668"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2891537"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3003133"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3001195"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301485"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/326"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403358"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301890"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3019497"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330660"},{"key":"ref40","first-page":"841","article-title":"N-GCN: Multi-scale graph convolution for semi-supervised node classification","volume-title":"Proc. 35th Uncertainty Artif. Intell. Conf.","volume":"115","author":"Abu-El-Haija"},{"key":"ref41","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","volume":"27","author":"Sutskever"},{"key":"ref42","first-page":"1","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","volume-title":"Proc. NIPS Workshop Deep Learn.","author":"Chung"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2966319"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5758"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380186"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/9916643\/09774997.pdf?arnumber=9774997","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T23:17:04Z","timestamp":1705965424000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9774997\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10]]},"references-count":45,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tits.2022.3167019","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10]]}}}