Moving-window GPR for nonlinear dynamic system modeling with dual updating and dual preprocessing
The characteristics of nonlinearity and time-varying changes in most industrial processes usually cripple the predictive performance of conventional soft sensors. In this article, moving-window Gaussian process regression (MWGPR) is proposed to effectively capture the process dynamics and to model n...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/105944 http://hdl.handle.net/10220/16749 http://dx.doi.org/10.1021/ie201898a |