Paper Title:
Intelligent Control System Based on SVM Combined with Soft Sensor for Microbiological Fermentation
  Abstract

The accuracy of SVM in fermentation process is mainly impacted by two factors input variable selection and parameter setting in SVM training procedures. In this paper, a novel method is proposed to solve the problem. The selection problem of SVM parameters and input variables is considered as a compound optimization problem. A new compound optimal objective function based on Akaike information criterion is constructed. In this paper, we propose a new method of soft sensor constructed with generalized support vector machine for microbiological fermentation. Experiment results demonstrate this method is an effective approach for parameter selection and input variable selection and has good performance for soft sensor modeling in microorganism fermentation process.

  Info
Periodical
Edited by
Qi Luo
Pages
1185-1191
DOI
10.4028/www.scientific.net/AMM.20-23.1185
Citation
J. H. Wu, T. Cen, "Intelligent Control System Based on SVM Combined with Soft Sensor for Microbiological Fermentation ", Applied Mechanics and Materials, Vols. 20-23, pp. 1185-1191, 2010
Online since
January 2010
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