{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T03:22:30Z","timestamp":1778556150862,"version":"3.51.4"},"reference-count":63,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2020B0909050001"],"award-info":[{"award-number":["2020B0909050001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51609195"],"award-info":[{"award-number":["51609195"]}],"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":["U1811463"],"award-info":[{"award-number":["U1811463"]}],"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":[[2022,12]]},"DOI":"10.1109\/tits.2022.3199160","type":"journal-article","created":{"date-parts":[[2022,8,26]],"date-time":"2022-08-26T19:38:47Z","timestamp":1661542727000},"page":"23694-23707","source":"Crossref","is-referenced-by-count":113,"title":["Fine-Grained Vessel Traffic Flow Prediction With a Spatio-Temporal Multigraph Convolutional Network"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7470-3313","authenticated-orcid":false,"given":"Maohan","family":"Liang","sequence":"first","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1591-5583","authenticated-orcid":false,"given":"Ryan Wen","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan, China"}]},{"given":"Yang","family":"Zhan","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4293-4763","authenticated-orcid":false,"given":"Huanhuan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Engineering, Technology &#x0026; Maritime Operations, Liverpool John Moores University, Liverpool, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2886-6968","authenticated-orcid":false,"given":"Fenghua","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, 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 of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]}],"member":"263","reference":[{"key":"ref39","first-page":"1","article-title":"Spatio-temporal multi-graph convolution network for ride-hailing demand forecasting","author":"geng","year":"2019","journal-title":"Proc AAAI"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106292"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref32","first-page":"1","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","author":"li","year":"2018","journal-title":"Proc ICLR"},{"key":"ref31","first-page":"865","article-title":"Traffic flow prediction with big data: A deep learning approach","volume":"16","author":"lv","year":"2015","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2021.108803"},{"key":"ref37","article-title":"Random vector functional link network: Recent developments, applications, and future directions","author":"malik","year":"2022","journal-title":"arXiv 2203 11316"},{"key":"ref36","article-title":"Multi-modal graph interaction for multi-graph convolution network in urban spatiotemporal forecasting","author":"geng","year":"2019","journal-title":"arXiv 1905 11395"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2018.2867042"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1111\/0885-9507.00154"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.geomorph.2020.107055"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2006.888061"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2018.2841832"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2317985"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2018.03.001"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2935152"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2976053"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-019-01355-0"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317741"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2018.2854913"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2008.2011693"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3007809"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3002718"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.08.067"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3165886"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2022.3140529"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.01.010"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3028743"},{"key":"ref59","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"2016","journal-title":"Proc NIPS"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1159"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01443"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07075-x"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5598390"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_28"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.ins.2020.04.009","article-title":"Adaptively constrained dynamic time warping for time series classification and clustering","volume":"534","author":"huanhuan","year":"2020","journal-title":"Inf Sci"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2022.103659"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/317"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2950416"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.2997352"},{"key":"ref13","first-page":"1","article-title":"Analysis of freeway traffic time-series data by using box Jenkins techniques","author":"ahmed","year":"1979","journal-title":"Transp Res Rec"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.2994910"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-2070(00)00053-4"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(03)00004-4"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)0733-947X(2003)129:6(664)"},{"key":"ref18","first-page":"653","article-title":"Traffic flow prediction for road transportation networks with limited traffic data","volume":"16","author":"abadi","year":"2015","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/0191-2615(84)90002-X"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2021.07.024"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1017\/S0373463316000850"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2013.2267735"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.07.069"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3025856"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.009"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2560131"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.02.013"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-017-1491-2"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3026836"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s12530-018-9243-y"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2018.03.038"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301890"},{"key":"ref41","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc 5th Int Conf Learn Represent"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5438"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/9972869\/09868210.pdf?arnumber=9868210","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T19:24:31Z","timestamp":1672082671000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9868210\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12]]},"references-count":63,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tits.2022.3199160","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12]]}}}