Similarity based robust probability latent variable regression model and its kernel extension for process monitoring
Sign Up to like & getrecommendations! Published in 2017 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2016.12.011
Abstract: Abstract In most industries, process and quality measurements with outliers are often collected. The outliers would have negative influences on data-based modelling and process monitoring. In our previous work on probability latent variable regression (PLVR),… read more here.
Keywords: process; variable regression; probability; latent variable ... See more keywords
Latent variable regression for supervised modeling and monitoring
Sign Up to like & getrecommendations! Published in 2020 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2020.1003153
Abstract: A latent variable regression algorithm with a regularization term ( rLVR ) is proposed in this paper to extract latent relations between process data X and quality data Y. In rLVR, the prediction error between… read more here.
Keywords: variable regression; latent variable; regression supervised; monitoring ... See more keywords
Semi-Supervised Dynamic Latent Variable Regression for Prediction and Quality-Relevant Fault Monitoring
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Control Systems Technology"
DOI: 10.1109/tcst.2024.3350364
Abstract: 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… read more here.
Keywords: quality; fault monitoring; semi supervised; latent variable ... See more keywords