Hybrid model for main and side reactions of p-xylene oxidation with factor influence based monotone additive SVR

Abstract

Due to the complex mechanism of main and burning side reactions in the industrial p-xylene oxidation, its first principle based kinetic mechanism model is hard to be established. Meanwhile building a data-driven model may be also a big challenge, because of various industrial sample data issues such as incompleteness and noise. A hybrid model of industrial p-xylene oxidation, which is based on monotone additive support vector regression, is proposed and established by employing industrial sample data and factor influence information. In the hybrid model, the influence of reaction factors on the main and burning side reactions is investigated with two additive support vector regression (AddSVR) models and the factor influence information is integrated into the modeling process by adding extra constraints to the AddSVR models. The hybrid model presents a better prediction accuracy.