LS-SVM Based Software Sensor for Fed-batch Yeast Fermentation and Comparative Studies

ZHANG, Hongwei and VAGAPOV, Y. (2006). LS-SVM Based Software Sensor for Fed-batch Yeast Fermentation and Comparative Studies. In: 2006 IEEE International Conference on Electro/Information Technology. IEEE, 564-568.

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Abstract

Least square support vector machine (LS-SVM) is a very powerful tool for pattern recognition and function estimation. In this paper, LS-SVM has been used to construct software sensors in an application to a fed-batch yeast fermentation process. Comparisons have been made between results from LS-SVM and software sensors using multiway partial least squares (MPLS) and extended Kalman filters (EKF). The LS-SVM algorithm is introduced firstly and then applied to a yeast fed-batch fermentation process to provide soft-sensing facilities. The soft-sensing capabilities of the LS-SVM approach are found to compare favorably with the results using EKF and MPLS

Item Type:	Book Section
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Materials and Engineering Research Institute > Modelling Research Centre > Microsystems and Machine Vision Laboratory
Identification Number:	https://doi.org/10.1109/EIT.2006.252204
Page Range:	564-568
Depositing User:	Margaret Boot
Date Deposited:	25 Aug 2017 10:46
Last Modified:	18 Mar 2021 17:15
URI:	https://shura.shu.ac.uk/id/eprint/15469

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