A Hybrid of Artificial Fish Swarm Algorithm and Particle Swarm Optimization for Feedforward Neural Network Training
Huadong Chen1, Shuzong Wang, Jingxi Li, Yunfan Li
1Research Inst. of New Weaponry Technology & Application , Naval Univ. of Engineering
Available Online October 2007.
- 10.2991/iske.2007.174How to use a DOI?
- artificial fish-swarm algorithm; particle swarm optimization; artificial neural networks
A hybrid of artificial fish swarm algorithm (AFSA) and particle swarm optimization (PSO) is used to training feedforward neural network. After the two algorithms are introduced respectively, the hybrid algorithm based on the two is expressed. The hybrid not only has the artificial fish behaviors of swarm and follow, but also takes advantage of the information of the particle. An experiment with a function approximation is simulated, which proves that the hybrid is more effective than AFSA and PSO.
- © 2007, 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 - Huadong Chen AU - Shuzong Wang AU - Jingxi Li AU - Yunfan Li PY - 2007/10 DA - 2007/10 TI - A Hybrid of Artificial Fish Swarm Algorithm and Particle Swarm Optimization for Feedforward Neural Network Training BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 1025 EP - 1028 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.174 DO - 10.2991/iske.2007.174 ID - Chen2007/10 ER -