重庆大学学报：自然科学版2012，Vol.35Issue(2)：123-127,5.
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
摘要
Abstract
In order to increase the predictive precision of gaussian process regression based soft sensor, a composite gaussian process regression model is proposed. This model combines the outputs of several gaussian process models as the output according to the variances and the distribution of the outputs, which results in higher prediction accuracy and higher robustness than the single gaussian process model. The proposed composite gaussian process regression model is successfully applied to the prediction of silicon content in hot metal.关键词
高斯过程回归/Bootstrap/软传感器/参数估计/统计方法Key words
Gaussian process regression/Bootstrap/soft sensor/parameter estimation/statistic method分类
信息技术与安全科学引用本文复制引用
任江洪,陈韬,曹长修..混合高斯过程回归模型在铁水硅含量预报中的应用[J].重庆大学学报：自然科学版,2012,35(2):123-127,5.基金项目
重庆市科委自然科学基金资助项目 （）
