{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T13:02:52Z","timestamp":1793365372810,"version":"4.5.0"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"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":["61773324"],"award-info":[{"award-number":["61773324"]}],"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":["61572407"],"award-info":[{"award-number":["61572407"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Education","award":["106-2221-E-011-149-MY2"],"award-info":[{"award-number":["106-2221-E-011-149-MY2"]}]},{"name":"Ministry of Education","award":["108-2218-E-011-006"],"award-info":[{"award-number":["108-2218-E-011-006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2021,6,1]]},"DOI":"10.1109\/tkde.2019.2954510","type":"journal-article","created":{"date-parts":[[2019,11,20]],"date-time":"2019-11-20T16:13:15Z","timestamp":1574266395000},"page":"2412-2424","source":"Crossref","is-referenced-by-count":404,"title":["Deep Air Quality Forecasting Using Hybrid Deep Learning Framework"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8035-405X","authenticated-orcid":false,"given":"Shengdong","family":"Du","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7780-104X","authenticated-orcid":false,"given":"Tianrui","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6134-6094","authenticated-orcid":false,"given":"Yan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, Sichuan Province, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9978-0400","authenticated-orcid":false,"given":"Shi-Jinn","family":"Horng","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","author":"olah","year":"0"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref31","year":"0"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2005.06.042"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219822"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.06.049"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2310219"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2820119"},{"key":"ref10","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298932"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"ref13","article-title":"Deep learning for time-series analysis","author":"gamboa","year":"2017"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2823740"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3233\/AIS-2010-0061"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2014.07.051"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2008.07.020"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2629592"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788573"},{"key":"ref28","article-title":"Assessing Beijing's PM2. 5 pollution: Severity, weather impact, APEC and winter heating","volume":"471","author":"liang","year":"2015","journal-title":"Proceedings of the Royal Society A"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.12.017"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806222"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/S1352-2310(02)00857-9"},{"key":"ref6","first-page":"1","article-title":"Probabilistic dynamic causal model for temporal data","author":"zhou","year":"2015","journal-title":"Proc IEEE Int Conf Neural Netw"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/11550907_126"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2014.12.011"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783344"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488188"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2012.02.041"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2012.06.031"},{"key":"ref20","article-title":"A critical review of recurrent neural networks for sequence learning","author":"lipton","year":"2015"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-016-7812-9"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2014.01.008"},{"key":"ref24","first-page":"3995","article-title":"Deep convolutional neural networks on multichannel time series for human activity recognition","author":"yang","year":"2015","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-015-1955-3"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.188"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10735"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/9427778\/08907358.pdf?arnumber=8907358","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,6]],"date-time":"2022-12-06T17:40:04Z","timestamp":1670348404000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8907358\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,1]]},"references-count":37,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2019.2954510","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":[[2021,6,1]]}}}