Soft Sensors for Monitoring and Control of Industrial Processes (Advances in Industrial Control)

By L. Fortuna, S. Graziani, A. Rizzo, M. Xibilia. 2006

654 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/101ec480f73a739257d90bc1add1f9290cd2ca39

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Rui Alexandre de Matos Araújo
2. Francisco Alexandre A. Souza
3. Jérôme Mendes
4. Zhi-Hua Zhou
5. Bogdan Gabrys
6. Sibylle Strandt
7. Petr Kadlec
8. Zhiqiang Ge

Citations in the corpus

• Distribution-Free One-Pass Learning (2017, background): “- Debutanizer column [FGRX07] is, a real-world dataset which is a record of chemical reactions, with in total 2,394 data samples consisting of 7 different features.”
• Nonlinear Dynamic Soft Sensor Modeling With Supervised Long Short-Term Memory Network (2020, neutral): “Flowchart for the debutanizer column [30].”
• Review of soft sensor methods for regression applications (2016, methodology): “In [84; 1] a combination of three variable selection methods was used to select the variables.”
• Data-driven Soft Sensors in the process industry (2009, methodology): “For example, Nomikos and MacGregor (1995b) and Chen and Liu (2002) discuss SPC charts for batch control and the latter additionally proposes a dynamic approach by using time-lagged variables in the model.”