A nonlinear robust continuum regression(NLRCR)modeling method combing radial basis function(RBF)and robust continuum regression(RCR)is presented to solve the problem that RCR algorithm hard to build the nonlinear system modeling of high predicting precision.Firstly

this approach uses RBF to carry out mapping transformation from nonlinear sample data to high dimension eigen space.Then

RCR algorithm is used for building linear regression modeling in high dimension eigen space.Simulation experiment is performed to show the effectiveness of this method.And it is utilized to develop a soft sensor model for the gasoline dry point in delayed coking

and highly precise prediction results are obtained compared with RCR and RBF-PLS methods.