The Model of the Water Content of the Dregs in Rotary Dryer Kiln Based on SVM

Abstract

Based on analysis of the process of rotary dryer kiln, a soft- sensor model for water content of the dregs by using the support vector machines (SVM) is proposed. The parameters of SVM are optimized through the hybrid optimization algorithm which combines the genetic search with the local search, first the kernel function and SVM parameters are optimized roughly through genetic algorithm, after certain generations, the kernel parameter is fine adjusted by local linear search. Experiments of acquiring the sample data are designed and the soft-sensor model has been obtained and used successfully in the inference control of rotary dryer kiln. The proposed method can not only overcome the difficulty in determining the structure and parameters of using other models such as RBF model but also has better generalization performance than other models