Application of Gaussian Process Regression Model in Industry

Abstract

Gaussian process regression is a new machine learning method based on Bayesian theory and statistical learning theory It is suitable for dealing with complex regression problems such as high dimension, small sample and nonlinearity. In view of the complex characteristics of industrial processes, this paper not only summarizes the basic methods and main problems of Gaussian processes, but also summarizes the application and research results of its basic modeling, optimization, control and fault diagnosis. Finally, combining the international development and the author’s practical experience, the application prospect and development trend of Gaussian process model in industrial processes are summarized and prospected.