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

An improved PSO algorithm coupling with prior information for classification of large scale dataset

Authors
Juanjuan Tu, Wenlan Zhou, Hongmei Li
Corresponding Author
Juanjuan Tu
Available Online June 2015.
DOI
https://doi.org/10.2991/icecee-15.2015.263How to use a DOI?
Keywords
Particle Swarm Optimization; Prior Information; Classification
Abstract
An improved particle swarm optimization (PSO) algorithm coupling with prior information for classification of large scale dataset is proposed in this paper. The prior information derived from the data set is used to determine the initial position of the particles. In the new algorithm, neural network is first trained by improved PSO and then by back-propagation (BP). The prior information narrows the search space and guides the movement direction of the particles, so the convergence rate and the generalization performance are improved. Experimental results demonstrate that the new algorithm is more effective than traditional methods.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
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-15.2015.263How 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  - Juanjuan Tu
AU  - Wenlan Zhou
AU  - Hongmei Li
PY  - 2015/06
DA  - 2015/06
TI  - An improved PSO algorithm coupling with prior information for classification of large scale dataset
PB  - Atlantis Press
SP  - 1409
EP  - 1414
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.263
DO  - https://doi.org/10.2991/icecee-15.2015.263
ID  - Tu2015/06
ER  -