Integrated soft sensor using just-in-time support vector regression and probabilistic analysis for quality prediction of multi-grade processes

By Yi Liu, Junghui Chen. 2013

139 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/1a9f3bb0fedc18a13446a53841dec7e1ba9bca06

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. Shen Yin
2. Steven X. Ding
3. Okyay Kaynak
4. Zhiqiang Ge
5. Biao Huang
6. Jingwei Dong
7. Zhihuan Song
8. Yuchen Jiang

In Mechanical Engineering

1. Shen Yin
2. Steven X. Ding
3. Okyay Kaynak
4. Biao Huang
5. Zhiqiang Ge
6. Zhihuan Song
7. Zhiwei Gao
8. Haitao Zhao

Citations in the corpus

• A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes (2021, background): “Typical solutions proposed recently include just-in-time learning [69], [70], iterative learning [71], incremental learning”
• Data Mining and Analytics in the Process Industry: The Role of Machine Learning (2017, methodology): “Liu and Chen [223] proposed an integrated soft sensor by using just-in-time support vector regression method and carried out probabilistic analysis for quality prediction of multi-grade processes.”