Review of soft sensor methods for regression applications
By Francisco Alexandre A. Souza, Rui Alexandre de Matos Araújo, Jérôme Mendes. 2016
312 citations recorded by the source corpus.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/7cb17dfd1d1c50951116b05b1268325f6384975a
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In Control and Systems Engineering
Citations in the corpus
- A Survey on Deep Learning for Data-Driven Soft Sensors (2021, methodology): “Detailed review about conventional methods can be found in existing work, such as [7], [16], etc.”
- Explicit and interpretable nonlinear soft sensor models for influent surveillance at a full-scale wastewater treatment plant (2019, background): “In WWTPs, the hard-to-measure ariables are either associated with a long time-delay or high capial cost [5].”
- A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes (2021, background): “For instance, Chapter 2 of the recently published book [12] only covers deep learning-based approaches; In [17], only the regression-based approaches are investigated.”