Soft Sensor Technique based on Robust SVM

Support vector machine (SVM) is a modern machine learning method based on Vapnik´s statistical learning theory. In this paper, a robust regression support vector machine has been proposed as a tool to soft sensor technique, in which robust SVM is used to estimate variable which is highly nonlinear, then uses them to identify absorption stabilization system (ASS) process variable. Case studies are performed and indicate that the proposed method provides satisfactory performance with excellent approximation and generalization property, soft sensor technique based on robust SVM achieves superior performance to the conventional method based on neural networks