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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Veröffentlicht in:	Computers & chemical engineering Jg. 150; S. 107320
Hauptverfasser:	Yamaguchi, Takafumi, Yamashita, Yoshiyuki
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2021
Schlagworte:	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
Online-Zugang:	Volltext
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