Semi-Supervised Dynamic Latent Variable Regression for Prediction and Quality-Relevant Fault Monitoring

Supervised latent variable regression methods such as partial least squares (PLS) and dynamic PLS have found wide applications in data analytics, quality prediction, and fault monitoring in various industries. In this article, we tackle the unbalanced data problem of sparse quality measurement and a...

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Veröffentlicht in:	IEEE transactions on control systems technology 2024-07, Vol.32 (4), p.1156-1168
Hauptverfasser:	Liu, Qiang, Yang, Chao, Qin, S. Joe
Format:	Artikel
Sprache:	eng
Schlagworte:	Data models Dynamic latent variable regression (DLVR) Fault detection fault monitoring Laplace equations Laplacian manifold regularization Manifolds Monitoring Prediction algorithms Predictive models Process controls Quality assessment quality prediction Regression Regularization semi-supervised learning (SSL) Semisupervised learning Statistical analysis
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