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A multi-task learning approach for chemical process abnormi..:
Zhao, Wenlei
;
Li, Jince
;
Li, Hongguang
Chemometrics and Intelligent Laboratory Systems. 233 (2023) - p. 104719 , 2023
Link:
https://doi.org/10.1016/j.chemolab.2022.104719
RT Journal T1 <Title>A multi-task learning approach for chemical process abnormity locations and fault classifications</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.chemolab.2022.104719&Exemplar=1&LAN=DE A1 Zhao, Wenlei A1 Li, Jince A1 Li, Hongguang PB Elsevier BV YR 2023 SN 0169-7439 JF Chemometrics and Intelligent Laboratory Systems VO 233 SP 104719 LK http://dx.doi.org/https://doi.org/10.1016/j.chemolab.2022.104719 DO https://doi.org/10.1016/j.chemolab.2022.104719 SF ELIB - SuUB Bremen
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