Semi-Supervised Deep Conditional Variational Autoencoder for Soft Sensor Modeling

Variational autoencoder (VAE) as an unsupervised deep generated model has been widely applied to process modeling for industrial processes due to its excellent ability in nonlinear and uncertain feature extraction. However, soft sensor based on VAE model faces three challenges. First, the constructe...

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Veröffentlicht in:	IEEE sensors journal Jg. 24; H. 5; S. 7153 - 7164
Hauptverfasser:	Tang, Xiaochu, Yan, Jiawei, Li, Yuan, Zhang, Xinmin, Song, Zhihuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Data mining Data models Decoding Deep learning Feature extraction Labels Machine learning Modelling semi-supervised (SS) model Sensors soft sensor Soft sensors supervised conditional variational autoencoder (VAE)
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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