In order to use the properties of samples

a soft-sensing method with multiple models based on an online clustering arithmetic and v-support vector regression(vSVR) was presented.The parameter selection of vSVR is improved faster and robust by a new cross validation method using the online clustering arithmetic and parameter’s prior knowledge.The proposed soft-sensing method was used to predict the light naphtha end point in hydrocracker fractionators.Practical applications indicated the proposed method was useful for the online prediction of quality specifications in chemical processes.