Support vector machine dynamic modeling method and its application in the fermentation process

The modeling for fermentation process has important significance in achieving control and optimal control of the fermentation process. Generalization capability of the model based on global learning support vector machine was not strong, so according to local learning theory the method of establishing the fermentation process dynamic model was proposed in this paper. The dynamic of the fermentation process model was realized through establishing the fermentation process dynamic sample sets. The method was used in the penicillin fermentation process and the process of Escherichia coli producing interleukin-2. Experimental results showed that the established dynamic model had a higher accuracy and a better dynamic adaptability compared with the static SVM model.