Research on Soft Sensor Modeling of Fermentation Process Based on v -SVR
Support vector regression (SVR) is a novel type of learning machine, which has shown to provide better generalization performance than traditional techniques. This thesis introduces a new type of support vector machine for regression (v-SVR), which based on SVR. The new algorithm can control the accuracy of fitness and prediction error by adjusting the parameter v. In the experiments v-SVR is used for soft sensor modeling of fermentation process. The results show that v-SVR has low error rate and better generalization with appropriate v.
soft sensor model fermentation SVR Polylysine.
Yongjun Ma
College of Computer Science and Information Engineering Tianjin University of Science and Technology Tianjin, China
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
759-763
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）