Abstract
According to the characteristics of biochemical processes, this paper studied the small samples of the data process. Small amount of data can be quickly measured variable modeling. Introduces the support vector machine (SVM) modeling as small sample theory, the least squares support vector machine (LS-SVM) algorithm based on improved SVM applied to the typical fermented penicillin biochemical processes in the past. Online prediction model only off-line testing of important process variables based on the simulation results simulation platform show that the method is only by learning the few batches of sample data. Establish a penicillin product concentration, cell concentration and substrate concentration. This paper analyzes the characteristics of the penicillin fermentation process, and the use of SVM method for modeling, give potency relationship between the factors and its influence. Through experiments, the influence of SVM model parameters to adjust performance. Through a variety of models from the established field data can be found, SVM is better than ANN modeling.
