A Framework and Modeling Method of Data-Driven Soft Sensors Based on Semisupervised Gaussian Regression
Author:
Affiliation:
1. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
Funder
National Natural Science Foundation of China
Publisher
American Chemical Society (ACS)
Subject
Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.5b04118
Reference26 articles.
1. Data-driven Soft Sensors in the process industry
2. Adaptive soft sensor for online prediction and process monitoring based on a mixture of Gaussian process models
3. Soft sensing modeling based on support vector machine and Bayesian model selection
4. A systematic approach for soft sensor development
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