Soft sensor modeling based on Gaussian processes^①

来源期刊：中南大学学报(英文版)2005年第4期

论文作者：熊志化 黄国宏 邵惠鹤

文章页码：469 - 471

Key words：Gaussian processes, soft sensor, modeling, kernel methods

Abstract: In order to meet the demand of online optimal running, a novel soft sensor modeling approach based on Gaussian processes was proposed. The approach is moderately simple to implement and use without loss of performance. It is trained by optimizing the hyperparameters using the scaled conjugate gradient algorithm with the squared exponential covariance function mployed. Experimental simulations show that the soft sensor modeling approach has the advantage via a real-world example in a refinery. Meanwhile, the method opens new possibilities for application of kernel methods to potential fields.