Study on soft sensing of glutamic acid fermentation process based on LS-SVM

Based on the in-depth study of the biochemical reaction mechanism of glutamate fermentation process, this paper expounds the process characteristics of fermentation process, introduces the research status of fermentation engineering soft sensing technology, and deeply analyzes the relevant factors affecting the formation of glutamate. On this basis, using the soft sensing method, a support vector machine soft sensing model based on fuzzy reasoning is proposed, and they are simulated, calculated, analyzed and compared respectively, so as to verify the effectiveness of the method. The main research contents are as follows: 1) A soft sensing model based on support vector machine (SVM) is established. Support vector machine is an algorithm based on the principle of structural risk minimization. It has stronger generalization ability than other nonlinear function approximation methods. 2) By using particle swarm optimization algorithm to optimize the key parameters of support vector machine, the prediction accuracy is further improved. 3) Using fuzzy reasoning mechanism and fuzzy basis function to modify the kernel function of support vector machine, compared with before, the anti-interference ability of the improved vector machine is greatly enhanced and the adaptability is further improved.