| 基于自适应遗传算法的RBF神经网络优化算法 |
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| 引用本文： | 鲍文胜,刘晓刚.基于自适应遗传算法的RBF神经网络优化算法[J].山东师范大学学报(自然科学版),2007,22(3):37-39. |
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| 作者姓名： | 鲍文胜 刘晓刚 |
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| 作者单位： | 1. 青岛大学师范学院,266071,山东青岛
2. 青岛大学信息工程学院,266071,山东青岛 |
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| 摘 要： | 针对传统遗传算法收敛速度慢的缺点,本文将改进后的遗传算法应用于RBF神经网络,对隐层中心和宽度值进行同步优化,并在复杂非线性函数的逼近实验中证明了本文算法相比传统遗传算法在搜索全局最小点的速度上得到了很大提高.
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| 关 键 词： | RBF神经网络 自适应遗传算法 函数逼近 |
| 修稿时间： | 2007-03-06 |
STRUCTURE OPTIMIZATION ALGORITHM OF RBF NEURAL NETWORKS BASED ON ADAPTIVE GENETIC ALGORITHM |
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| Bao Wensheng,Liu Xiaogang.STRUCTURE OPTIMIZATION ALGORITHM OF RBF NEURAL NETWORKS BASED ON ADAPTIVE GENETIC ALGORITHM[J].Journal of Shandong Normal University(Natural Science),2007,22(3):37-39. |
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| Authors: | Bao Wensheng Liu Xiaogang |
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| Abstract: | Adaptive probability of crossover and mutation are used in this paper and they can adjust themselves according to the fitness function, so that this approach can solve the problem that the traditional genetic algorithm converges into minimum points slowlty. We optimize the centers and widths of RBF neural network constructed in the method this paper presented. The experiments of the approximation of nonlinear function indicate that the speed in sddking minimum points of this method is greatly improved compared with that of traditional genetic algorithm. |
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| Keywords: | RBF neural network adaptive genetic algorithm approximation of function |
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