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A SVR-Based Multiple Modeling Algorithm for Antibiotic Fermentation Process Using FCM

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3498))

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Abstract

A multiple modeling algorithm for antibiotic fermentation process based on fuzzy c-means (FCM) and support vector regression (SVR) is proposed. By analyzing the features of antibiotic fermentation, the mechanism of multiple modeling of the bioprocess is presented. Using FCM clustering method, the bioprocess is classified into several work states and sub-models. Then, taking advantage of the generalization properties of SVR, the multiple model of bioprocess is established and the proposed algorithm is described. Experimental data of industrial penicillin production is used to validate the model.

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Author information

Authors and Affiliations

  1. Department of Automation, Shanghai Jiao Tong University, Shanghai, 200030, China

    Yaofeng Xue & Jingqi Yuan

  2. State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, 200237, China

    Jingqi Yuan

Authors
  1. Yaofeng Xue
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  2. Jingqi Yuan
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Xue, Y., Yuan, J. (2005). A SVR-Based Multiple Modeling Algorithm for Antibiotic Fermentation Process Using FCM. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_110

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  • DOI: https://doi.org/10.1007/11427469_110

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25914-5

  • Online ISBN: 978-3-540-32069-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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