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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Bibliographic Details

Published in:	ISA transactions
Main Authors:	He, Yan-Lin, Jiang, Yu, Gao, Hui-Hui, Xu, Yuan, Zhu, Qun-Xiong
Format:	Journal Article
Language:	English
Published:	United States Elsevier Ltd 04.06.2025
Subjects:	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 Access:	Get full text
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