Novel semi-supervised sparse stacked autoencoder integrated with local linear embedding for industrial soft sensing

Data-driven industrial soft sensor modeling techniques have been widely applied in predicting key variables in complex industrial processes. However, with industrial processes becoming increasingly intricate, the data they produce exhibit characteristics such as strong temporal dependencies, high di...

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Veröffentlicht in:	ISA transactions
Hauptverfasser:	He, Yan-Lin, Jiang, Yu, Gao, Hui-Hui, Xu, Yuan, Zhu, Qun-Xiong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 04.06.2025
Schlagworte:	Data-driven modelling Industrial processes Industrial soft sensors Local features Industrial processes Industrial soft sensors Local features Data-driven modelling
ISSN:	0019-0578, 1879-2022, 1879-2022
Online-Zugang:	Volltext
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