Research on SVM Cell Concentration Prediction of Erythromycin Fermentation Process Based on Ant Colony Optimization

Li Tian; Qiang Qiang Wang; An Zhao Cao

doi:10.4028/www.scientific.net/AMR.734-737.2998

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 734-737Research on SVM Cell Concentration Prediction of...

Research on SVM Cell Concentration Prediction of Erythromycin Fermentation Process Based on Ant Colony Optimization

Abstract:

Due to disadvantages of nonlinear, complexity and uncertainty of fermentation process, a research on cell concentration prediction of erythromycin fermentation process was carried out. Combining the optimization ability of ant colony algorithm and the regression ability of support vector machine, an ACO-SVM model is built. Case study shows that, the model is more accurate and more effective for the cell concentration prediction than ANN and SVM model.

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Periodical:

Advanced Materials Research (Volumes 734-737)

Pages:

2998-3002

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.734-737.2998

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Online since:

August 2013

Authors:

Li Tian, Qiang Qiang Wang, An Zhao Cao

Keywords:

Ant Colony Optimization Algorithm (ACOA), Erythromycin Fermentation, Support Vector Machine (SVM)

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