摘要
人工鱼群算法是一种新型的寻优策略,将人工鱼群算法用于RBF神经网络的训练过程,建立了相应的优化模型,算法与BP算法、RBF算法进行比较,结果表明人工鱼群算法具有鲁棒性强,全局收敛性好,以及对初值的不敏感等特点。
Artificial fish-swarm algorithm （AFSA） is a novel optimizing method proposed lately. An Artificial Fish-swarm Algorithm （AFSA） for the RBF neural networks and a model based on this method were presented of the first time here. Compared with the Back-propagation Algorithm added momentum and the RBF Algorithm, optimization result of RBF neural networks by AFSA demonstrates that AFSA has a strong robustness and good global astringency. AFSA is also proved to be initial values.
出处
《东北电力大学学报》
2006年第4期23-27,共5页
Journal of Northeast Electric Power University
