Quality prediction for multi-grade batch process using sparse flexible clustered multi-task learning

Data-driven quality prediction methods are widely used in industrial chemical plants. However, it is often difficult to develop prediction models for multi-grade batch processes. Two major issues need to be considered when developing high-accuracy models. The first is the unavailability of sufficien...

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Vydané v:	Computers & chemical engineering Ročník 150; s. 107320
Hlavní autori:	Yamaguchi, Takafumi, Yamashita, Yoshiyuki
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.07.2021
Predmet:	Clustered multi-task learning Multi-grade batch process Quality prediction Sparse regularization Sparse regularization Clustered multi-task learning Multi-grade batch process Quality prediction
ISSN:	0098-1354
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