A novel semi-supervised pre-training strategy for deep networks and its application for quality variable prediction in industrial processes

Title
A novel semi-supervised pre-training strategy for deep networks and its application for quality variable prediction in industrial processes
Authors
Keywords
Quality prediction, Soft sensor, Deep learning, Stacked autoencoder (SAE), Semi-supervised SAE (SS-SAE)
Journal
CHEMICAL ENGINEERING SCIENCE
Volume 217, Issue -, Pages 115509
Publisher
Elsevier BV
Online
2020-01-26
DOI
10.1016/j.ces.2020.115509

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