{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T03:06:45Z","timestamp":1775099205425,"version":"3.50.1"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T00:00:00Z","timestamp":1564617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T00:00:00Z","timestamp":1564617600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T00:00:00Z","timestamp":1564617600000},"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":["61703367"],"award-info":[{"award-number":["61703367"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Ind. Electron."],"published-print":{"date-parts":[[2019,8]]},"DOI":"10.1109\/tie.2018.2874589","type":"journal-article","created":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T18:42:18Z","timestamp":1539369738000},"page":"6362-6373","source":"Crossref","is-referenced-by-count":52,"title":["Parallel Computing and SGD-Based DPMM For Soft Sensor Development With Large-Scale Semisupervised Data"],"prefix":"10.1109","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1291-3072","authenticated-orcid":false,"given":"Weiming","family":"Shao","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0881-213X","authenticated-orcid":false,"given":"Le","family":"Yao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7828-0856","authenticated-orcid":false,"given":"Zhiqiang","family":"Ge","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4098-6479","authenticated-orcid":false,"given":"Zhihuan","family":"Song","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2017.02.002"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.03.008"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2017.2759900"},{"key":"ref32","first-page":"639","article-title":"A constructive definition of Dirichlet priors","volume":"4","author":"sethuraman","year":"1994","journal-title":"Statist Sinica"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1214\/06-BA104"},{"key":"ref30","author":"bishop","year":"2006","journal-title":"Pattern Recognition and Machine Learning"},{"key":"ref37","year":"2018"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1109\/JPROC.2015.2388958","article-title":"Big data for modern industry: Challenges and trends","volume":"103","author":"yin","year":"0","journal-title":"Proc IEEE"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2014.01.003"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2017.03.032"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2016.2579609"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2016.2608914"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1021\/ie3020186"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2016.04.033"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2014.07.013"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2016.2576999"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1002\/aic.12422"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2015.08.002"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2733448"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2013.08.005"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2017.2654552"},{"key":"ref28","first-page":"908","article-title":"Semi-supervised regression with co-training","author":"zhou","year":"0","journal-title":"Proc 19th Int Joint Conf Artif Intell"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2733443"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2307349"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2018.01.008"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2018.2799618"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1002\/aic.14270"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CCTA.2017.8062517"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2013.2248155"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ces.2012.07.018"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.iecr.8b02913"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2505086"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2756872"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2017.8037512"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1002\/aic.14523"},{"key":"ref21","first-page":"77","article-title":"Semisupervised learning scheme using Dirichlet process EM-algorithms","volume":"108","author":"kimura","year":"2009","journal-title":"IEICE Tech Rep"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2018.04.004"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2017.2658732"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1021\/acs.iecr.5b04118"},{"key":"ref25","first-page":"1303","article-title":"Stochastic vairational inference","volume":"14","author":"hoffman","year":"2013","journal-title":"J Mach Learn Res"}],"container-title":["IEEE Transactions on Industrial Electronics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/41\/8678530\/08490899.pdf?arnumber=8490899","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:52:33Z","timestamp":1657745553000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8490899\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":40,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tie.2018.2874589","relation":{},"ISSN":["0278-0046","1557-9948"],"issn-type":[{"value":"0278-0046","type":"print"},{"value":"1557-9948","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8]]}}}