Research on Modeling and Process Parameters Optimization of GlcN Fermentation Process

Authors

Wanli Yu, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Wang Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Zhicheng Ji, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: In view of the high price and low detection accuracy of biosensors, which makes it difficult to obtain accurate and real-time biological parameters in the process of GlcN fermentation, the Least Square Support Vector Machine (LSSVM) model is established to predict the cell concentration, product concentration and substrate concentration. In order to improve the accuracy of the prediction model, the improved multiverse optimization algorithm based on Levy flight is utilized to optimize several parameters of the LSSVM model. On the basis of the model aiming at the maximum product concentration at the time of fermentation completion, the fermentation process parameters are optimized by the improved multiverse optimization algorithm. The simulation results show that the method achieves higher modeling accuracy and improves the final fermentation product concentration.

Recommended Citation

Yu, Wanli; Yan, Wang; and Ji, Zhicheng (2020) "Research on Modeling and Process Parameters Optimization of GlcN Fermentation Process," Journal of System Simulation: Vol. 32: Iss. 10, Article 6.
DOI: 10.16182/j.issn1004731x.joss.20-FZ0400
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss10/6

First Page

1895

Revised Date

2020-06-23

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-FZ0400

Last Page

1902

CLC

TP391.9

Recommended Citation

Yu Wanli, Wang Yan, Ji Zhicheng. Research on Modeling and Process Parameters Optimization of GlcN Fermentation Process[J]. Journal of System Simulation, 2020, 32(10): 1895-1902.

DOI

10.16182/j.issn1004731x.joss.20-FZ0400