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作者:

Gao, Xue-Jin (Gao, Xue-Jin.) (学者:高学金) | Wang, Pu (Wang, Pu.) | Sun, Chong-Zheng (Sun, Chong-Zheng.) | Yi, Jian-Qiang (Yi, Jian-Qiang.) | Zhang, Ya-Ting (Zhang, Ya-Ting.) | Zhang, Hui-Qing (Zhang, Hui-Qing.)

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摘要:

On the basis of the standard SVM for regression, the dynamic Ε-SVM method was proposed to establish precise mathematical models to describe the behavior of biochemistry systems, namely each training sample used different error. At the same time, an improved multi-objective Genetic Algorithm (MOGA) was used to automatically select the dynamic Ε-SVM parameters. A new modeling method that combined improved MOGA with dynamic Ε-SVM regression was presented. The model for titer pre-estimate was developed in Matlab6.5 with data collected from real plant. The model possessed the strong capability of fitting and generalization. It is shown that the method achieves significant improvement in the generalization performance in comparison with the modeling method based on MOGA and the standard SVM.

关键词:

Genetic algorithms Fermentation Biochemistry Mathematical models

作者机构:

  • [ 1 ] [Gao, Xue-Jin]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Wang, Pu]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Sun, Chong-Zheng]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Yi, Jian-Qiang]Key Laboratory of Complex System and Intelligence Science, Chinese Academy of Sciences, Beijing 100033, China
  • [ 5 ] [Zhang, Ya-Ting]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
  • [ 6 ] [Zhang, Hui-Qing]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China

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来源 :

Journal of Beijing University of Technology

ISSN: 0254-0037

年份: 2006

期: 5

卷: 32

页码: 405-409

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