Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering

Soft measurement of the cell concentration based on SVM and PSO

Authors
Hua Meng, Hui Gao, Liting Han
Corresponding Author
Hua Meng
Available Online August 2015.
DOI
10.2991/ic3me-15.2015.145How to use a DOI?
Keywords
Soft sensor ;SVM; cell concentration; PSO; fermentation
Abstract

The process of Pichia pastoris fermentation has a long period and less offline data . The cell concentration and some other important variables can not be measured on line. The soft sensor modeling at present is mainly the artificial neural network (ANN).This paper introduces the Support Vector Machine (SVM). Selected fewer off line data and established soft sensor modeling about cell concentration. To address the difficulty of parameters selection in SVM, parameters was optimized by using Particle Swarm Optimization (PSO) , Simulation experiment proves that the support vector machine has better prediction effect and generalization ability and PSO can quickly find out the best parameters of SVM..

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
Series
Advances in Engineering Research
Publication Date
August 2015
ISBN
978-94-6252-100-1
ISSN
2352-5401
DOI
10.2991/ic3me-15.2015.145How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hua Meng
AU  - Hui Gao
AU  - Liting Han
PY  - 2015/08
DA  - 2015/08
TI  - Soft measurement of the cell concentration based on SVM and PSO
BT  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 747
EP  - 750
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.145
DO  - 10.2991/ic3me-15.2015.145
ID  - Meng2015/08
ER  -