An improved PSO algorithm coupling with prior information for classification of large scale dataset
Juanjuan Tu, Wenlan Zhou, Hongmei Li
Available Online June 2015.
- https://doi.org/10.2991/icecee-15.2015.263How to use a DOI?
- Particle Swarm Optimization; Prior Information; Classification
- 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.
- 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 -