混合高斯过程回归模型在铁水硅含量预报中的应用 = Composite gaussian process regression model and its application to prediction of silicon content in hot metal
为了提高基于高斯过程回归的软测量模型的预测精度,提出了一种混合高斯过程回归模型。该模型将高斯过程回归模型预测输出值的方差及其分布作为主要考虑因素,对多个高斯过程回归模型的输出值进行组合输出,获得了比单个高斯过程回归模型更高的预测精度和更强的模型鲁棒性。将该模型实用于高炉铁水硅含量预报模型的建模,获得了比使用单个高斯过程回归模型建模时更好的应用效果。In order to increase the predictive precision of gaussian process regression based soft sensor, a composite gaussian process...
Saved in:
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | Chinese Chinese |
| Published: |
2015
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/107138 http://hdl.handle.net/10220/25398 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | Chinese Chinese |