Supervised and semi-supervised probabilistic learning with deep neural networks for concurrent process-quality monitoring-Reference-Cited by-同舟云学术

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Supervised and semi-supervised probabilistic learning with deep neural networks for concurrent process-quality monitoring

Published:2021-04 Issue: Volume:136 Page:54-62
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Wang Kai^ORCID,Yuan Xiaofeng,Chen Junghui^ORCID,Wang Yalin

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference34 articles.

1. Overfitting in neural nets: Backpropagation, conjugate gradient, and early stopping;Caruana,2001

2. Weighted semi-supervised Orthogonal Factor Analysis Model for Quality-related Process Monitoring;Cui,2018

3. Tutorial on variational autoencoders;Doersch,2016

4. Process data analytics via probabilistic latent variable models:A tutorial review;Ge;Industrial and Engineering Chemistry Research,2018

5. Supervised linear dynamic system model for quality related fault detection in dynamic processes;Ge;Journal of Process Control,2016

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