Comparison Studies of LS_SVM and SVM on Modeling for Fermentation Processes

The SVM needs use approximation accuracy ε, however the LS_SVM (least square support vector machine) doesn’t need ε. According to these characteristics, this paper studies the fitting and generalization capabilities of models that LS_SVM and SVM establishes for the penicillin fermentation processes respectively. An improved GA selects the parameter values for LS_SVM and SVM respectively. The experiment shows the model based on LS_SVM possesses the strong capabilities of fitting and generalization. If ε is too large, the capabilities of fitting and generalization of model based on SVM are not high; if ε is too small, the capabilities of fitting and generalization are relatively high, but the modeling process demands more long time. So, the LS_SVM is more suitable for modeling in fermentation processes.