{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T02:42:54Z","timestamp":1776134574701,"version":"3.50.1"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2017YFC0803903"],"award-info":[{"award-number":["2017YFC0803903"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2929692","type":"journal-article","created":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T23:20:52Z","timestamp":1563837652000},"page":"98053-98060","source":"Crossref","is-referenced-by-count":102,"title":["T-LSTM: A Long Short-Term Memory Neural Network Enhanced by Temporal Information for Traffic Flow Prediction"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1551-4448","authenticated-orcid":false,"given":"Luntian","family":"Mou","sequence":"first","affiliation":[]},{"given":"Pengfei","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Haitao","family":"Xie","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7068-4669","authenticated-orcid":false,"given":"Yanyan","family":"Chen","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3390\/s17040818"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1049\/iet-its.2016.0257"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.10.025"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2016.09.002"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2010.10.004"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1049\/iet-its.2011.0123"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2018.03.001"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.01.015"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2014.2311123"},{"key":"ref34","first-page":"1096","article-title":"Unsupervised feature learning for audio classification using convolutional deep belief networks","author":"lee","year":"2009","journal-title":"Proc NIPS"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/SmartCity.2015.63"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2845863"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.08.067"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(02)00009-8"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2011.12.006"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/MITS.2014.2332591","article-title":"A comparison of detrending models and multi-regime models for traffic flow prediction","volume":"6","author":"li","year":"2014","journal-title":"IEEE Intell Transp Syst Mag"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2457240"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2019.03.022"},{"key":"ref17","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":"ref18","first-page":"22","article-title":"Short-term traffic and travel time prediction models","volume":"43","author":"van lint","year":"2012","journal-title":"Transp Res Circular"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2014.01.005"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.07.069"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1109\/JAS.2016.7508798","article-title":"Traffic signal timing via deep reinforcement learning","volume":"3","author":"li","year":"2016","journal-title":"IEEE\/CAA Journal of Automatica Sinica"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1080\/18128600902823216"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2513086"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/YAC.2016.7804912"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbspro.2013.08.076"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2017.7510316"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref7","first-page":"16","article-title":"Prediction of recreational travel using genetically designed regression and time-delay neural network models","volume":"1805","author":"lingras","year":"2002","journal-title":"IEEE\/CAA Journal of Automatica Sinica"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2480157"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2015.03.014"},{"key":"ref1","first-page":"643","article-title":"Deep learning for control: The state of the art and prospects","volume":"42","author":"duan","year":"2016","journal-title":"ACTA Automatica Sinica"},{"key":"ref20","first-page":"1","article-title":"Analysis of freeway traffic time-series data by using box-Jenkins techniques","volume":"773","author":"ahmed","year":"1979","journal-title":"Transp Res Rec"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3141\/1678-22"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(97)82903-8"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.3141\/1776-01"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)0733-947X(2003)129:6(664)"},{"key":"ref41","first-page":"215","article-title":"Taxi demand prediction based on CNN-LSTM-ResNet hybrid depth learning model","volume":"18","author":"duan","year":"2018","journal-title":"J Transp Syst Eng Inf Technol"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"74","DOI":"10.3141\/1857-09","article-title":"Forecasting traffic flow conditions in an urban network: Comparison of multivariate and univariate approaches","volume":"1857","author":"yiannis","year":"2003","journal-title":"Transp Res Rec"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s00180-009-0152-1"},{"key":"ref43","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc ICLR"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2011.2158001"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08767922.pdf?arnumber=8767922","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T19:40:10Z","timestamp":1628624410000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8767922\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2929692","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}