【作者】 刘耀年； 姚玉萍； 李迎红； 刘俊峰；

【Author】 Liu Yaonian Yao Yuping Li Yinghong Liu Junfeng (Northeast China Institute of Electric Power Engineering,Jilin 132012)

【机构】 东北电力学院电气工程学院；

【摘要】 人工鱼群算法是一种新型的寻优策略,文中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。更多还原

【Abstract】 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.更多还原