Deep quality-related feature extraction for soft sensing modeling: A deep learning approach with hybrid VW-SAE

Soft sensors have been extensively used to predict difficult-to-measure quality variables for effective modeling, control and optimization of industrial processes. To construct accurate soft sensors, it is significant to carry out feature extraction for massive high-dimensional process data. Recentl...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 396; S. 375 - 382
Hauptverfasser:	Yuan, Xiaofeng, Ou, Chen, Wang, Yalin, Yang, Chunhua, Gui, Weihua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 05.07.2020
Schlagworte:	Deep learning Feature representation Hybrid variable-wise weighted SAE (HVW-SAE) Soft sensor Stacked autoencoder (SAE) Deep learning Stacked autoencoder (SAE) Soft sensor Hybrid variable-wise weighted SAE (HVW-SAE) Feature representation
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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