Batch process quality prediction based on denoising autoencoder-spatial temporal convolutional attention mechanism fusion network Batch process quality prediction based on denoising autoencoder-spatial temporal convolutional attention mechanism fusion network

In batch processes, the accurate prediction of quality variables plays a crucial role in smooth production and quality control. However, various sources of noise in the production environment cause abnormal data fluctuations that deviate from the real value. Coupled with the dynamic nonlinearity of...

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Veröffentlicht in:Applied intelligence (Dordrecht, Netherlands) Jg. 55; H. 7; S. 515
Hauptverfasser: Zhang, Yan, Cao, Jie, Zhao, Xiaoqiang, Hui, Yongyong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.05.2025
Springer Nature B.V
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ISSN:0924-669X, 1573-7497
Online-Zugang:Volltext
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