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Author:

Gao, Xuejin (Gao, Xuejin.) (Scholars:高学金) | Wang, Pu (Wang, Pu.) | Zhang, Yating (Zhang, Yating.) | Zhang, Huiqing (Zhang, Huiqing.) | Qi, Yongsheng (Qi, Yongsheng.) | Guan, Wei (Guan, Wei.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

To increase fermentation unit, the strategy of optimization control that combines the support vector machine (SVM) with genetic algorithm based on real coding (RGA) is proposed. To solve the coupling of fermentation parameters, the idea of pattern is also introduced. SVM establishes the prediction model for the microbial process, and RGA taking the model as fitness function calculates the optimal control pattern. The results show that the penicillin titer of fermentation process optimized is increased by 22.88% compared with that of fermentation process not optimized.

Keyword:

Fermentation Predictive analytics Genetic algorithms Process control Support vector machines Models Vector control (Electric machinery)

Author Community:

  • [ 1 ] [Gao, Xuejin]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Wang, Pu]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Zhang, Yating]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Zhang, Huiqing]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 5 ] [Qi, Yongsheng]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 6 ] [Guan, Wei]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Chemical Industry and Engineering (China)

ISSN: 0438-1157

Year: 2008

Issue: 6

Volume: 59

Page: 1462-1469

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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