Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics

The research of least squares support vector machine optimized by particle swarm optimization algorithm in the simulation MBR prediction

Authors
Weiwei Li, Chunqing Li, Jingyun Nie, Tao Wang
Corresponding Author
Weiwei Li
Available Online June 2015.
DOI
https://doi.org/10.2991/icecee-15.2015.195How to use a DOI?
Keywords
MBR; Membrane flux ; PCA; LSSVM; PSO
Abstract
This paper proposes an intelligent algorithm to predict the MBR membrane flux. The algorithm applies the least squares support vector machine (LS-SVM) to the research of MBR simulation prediction, optimize the penalty factor and kernel parameters of LS-SVM model by particle swarm optimization (PSO) for avoiding the blindness of artificial selection parameter. Due to the complexity and cross-cutting of the factors that affect MBR membrane fouling, first of all, we analyze the factors by principal component analysis (PCA), extract the important factors as the LS-SVM input layer, MBR membrane flux as output layer, and then create PSO-LSSVM prediction simulation model. In the end, we get predictive results with the model. By comparing the predicted results with experimental data, the algorithm has higher prediction accuracy for MBR membrane flux. To further verify the effectiveness of the algorithm, we also compare the model with BP neural network model, the results show that the prediction model of PSO-LSSVM has a higher prediction accuracy.
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Proceedings
2015 2nd International Conference on Electrical, Computer Engineering and Electronics
Part of series
Advances in Computer Science Research
Publication Date
June 2015
ISBN
978-94-62520-81-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/icecee-15.2015.195How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Weiwei Li
AU  - Chunqing Li
AU  - Jingyun Nie
AU  - Tao Wang
PY  - 2015/06
DA  - 2015/06
TI  - The research of least squares support vector machine optimized by particle swarm optimization algorithm in the simulation MBR prediction
BT  - 2015 2nd International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 1030
EP  - 1035
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.195
DO  - https://doi.org/10.2991/icecee-15.2015.195
ID  - Li2015/06
ER  -