Soft sensing modeling based on support vector machine and Bayesian model selection

By Weiwu Yan, Hui-he Shao, Xiaofan Wang. Computers and Chemical Engineering, 2004

315 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/c6d44c87176c16c3e6cf83908fef93e0d30543c7

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. Okyay Kaynak
2. Shen Yin
3. Yuchen Jiang
4. Jingwei Dong
5. Bogdan Gabrys
6. Sibylle Strandt
7. Petr Kadlec
8. Peng Shi

Citations in the corpus

• Data-driven Soft Sensors in the process industry (2009, methodology): “Application aspects of the SVM are discussed in Yan et al. (2004); Feng et al. (2003); Li and Li (2005).”
• A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes (2021, methodology): “procedures, such as random forest and generic algorithm [60],”