{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T21:39:49Z","timestamp":1793482789725,"version":"4.5.0"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2021,5,1]],"date-time":"2021-05-01T00:00:00Z","timestamp":1619827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,5,1]],"date-time":"2021-05-01T00:00:00Z","timestamp":1619827200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,5,1]],"date-time":"2021-05-01T00:00:00Z","timestamp":1619827200000},"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":["61590921"],"award-info":[{"award-number":["61590921"]}],"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":["61860206014"],"award-info":[{"award-number":["61860206014"]}],"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":["U1911401"],"award-info":[{"award-number":["U1911401"]}],"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":["61703440"],"award-info":[{"award-number":["61703440"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R&amp;D Program of China","award":["2018YFB1701100"],"award-info":[{"award-number":["2018YFB1701100"]}]},{"name":"National Key R&amp;D Program of China","award":["2018AAA0101603"],"award-info":[{"award-number":["2018AAA0101603"]}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2018JJ3687"],"award-info":[{"award-number":["2018JJ3687"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Ind. Electron."],"published-print":{"date-parts":[[2021,5]]},"DOI":"10.1109\/tie.2020.2984443","type":"journal-article","created":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T15:57:40Z","timestamp":1586447860000},"page":"4404-4414","source":"Crossref","is-referenced-by-count":497,"title":["Deep Learning With Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development"],"prefix":"10.1109","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9072-7179","authenticated-orcid":false,"given":"Xiaofeng","family":"Yuan","sequence":"first","affiliation":[{"name":"School of Automation, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1626-2713","authenticated-orcid":false,"given":"Lin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9311-7739","authenticated-orcid":false,"given":"Yuri A. W.","family":"Shardt","sequence":"additional","affiliation":[{"name":"Department of Automation Engineering, Technical University of Ilmenau, Ilmenau, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1876-7707","authenticated-orcid":false,"given":"Yalin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2550-1509","authenticated-orcid":false,"given":"Chunhua","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2014","journal-title":"Comput Sci"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ASRU.2013.6707742"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/978-3-642-24797-2_2","article-title":"Supervised sequence labelling with recurrent neural networks","volume":"385","author":"graves","year":"2008","journal-title":"Studies Comput Intell"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2938890"},{"key":"ref37","first-page":"669","article-title":"Applying LSTM to time series predictable through time-window approaches","author":"gers","year":"2001","journal-title":"Proc Int Conf Artif Neural Netw"},{"key":"ref36","first-page":"244","article-title":"Language modeling with highway LSTM","author":"kurata","year":"0","journal-title":"Proc ASRU 2017"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1002\/cjce.23665"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2902129"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2016.2610839"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/366"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2014.2385042"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2016.08.014"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2019.103921"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1002\/cem.3185"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2020.2985614"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2005.12.001"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.10.039"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2007.09.004"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2809730"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.isatra.2019.07.001","article-title":"A novel deep learning based fault diagnosis approach for chemical process with extended deep belief network","volume":"96","author":"wang","year":"2020","journal-title":"ISA T"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2016.2527621"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.03.018"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2951708"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2016.2579609"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2016.2622668"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2018.2810678"},{"key":"ref8","first-page":"403","article-title":"Temperature prediction for roller kiln based on hybrid first-principle model and data-driven MW-DLWKPCR model","volume":"98","author":"dai","year":"2020","journal-title":"ISATA"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.cherd.2015.01.006"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2013.05.007"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-21509-9"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2733443"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/DDCLS.2018.8516025"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.jprocont.2014.01.012","article-title":"Data-driven soft sensor development based on deep learning technique","volume":"24","author":"chao","year":"2014","journal-title":"J Process Control"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1002\/cem.3040"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1080\/00207178608933633"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/I2MTC.2017.7969924"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1080\/00207178608933593"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.11.107"},{"key":"ref42","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"0","journal-title":"Proc 27th Int Conf Neural Inf Process Syst"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2733448"},{"key":"ref41","first-page":"2204","article-title":"Recurrent models of visual attention","author":"mnih","year":"0","journal-title":"Proc 27th Int Conf Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2957366"},{"key":"ref44","article-title":"Adam: A method for stochastic optimization[J]","author":"kingma","year":"2014"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2880968"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-4012"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ces.2020.115509"}],"container-title":["IEEE Transactions on Industrial Electronics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/41\/9350527\/09062588.pdf?arnumber=9062588","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T10:49:18Z","timestamp":1652179758000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9062588\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5]]},"references-count":48,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tie.2020.2984443","relation":{},"ISSN":["0278-0046","1557-9948"],"issn-type":[{"value":"0278-0046","type":"print"},{"value":"1557-9948","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5]]}}}