| 引用本文: | 石红端,刘 勇,刘宝坤,李光泉.基于混合递阶遗传算法的径向基神经网络学习算法及其应用[J].控制理论与应用,2002,19(4):627~630.[点击复制] |
| SHI Hong-rui,LIU Yong,LIU Bao-kun,LI Guang-quan.RBFNN algorithm based on hybrid hierarchy genetic algorithm and its application[J].Control Theory and Technology,2002,19(4):627~630.[点击复制] |
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| 基于混合递阶遗传算法的径向基神经网络学习算法及其应用 |
| RBFNN algorithm based on hybrid hierarchy genetic algorithm and its application |
| 摘要点击 1767 全文点击 1707 投稿时间：1999-11-29 修订日期：2001-05-31 |
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| DOI编号 |
| 2002,19(4):627-630 |
| 中文关键词 径向基神经网络 混合递阶遗传算法 混沌时间序列 |
| 英文关键词 radial basis function neural network hybrid hierarchy genetic algorithms Chaos time series |
| 基金项目 |
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| 中文摘要 |
| 在研究径向基神经网络学习算法的基础上, 提出了一种新型的径向基神经网络学习算法———混合递阶遗传算法. 该算法将递阶遗传算法和最小二乘法的优点结合在一起, 能够同时确定径向基神经网络的结构和参数, 并具有较高的学习效率. 采用基于混合递阶遗传算法的径向基神经网络对混沌时间序列学习和预测, 取得了较好的效果. |
| 英文摘要 |
| Based on the study of RBFNN (radial basis function neural network) training algorithm and genetic algorithm, a new RBFNN training algorithm-hybrid hierarchy genetic algorithm is introduced by combining hierarchy genetic algorithm and least-square method. The hybrid algorithm greatly increases the training speed while is still able to determine the structure and parameters of the RBFNN from sample data. The new training algorithm is used to identify and predict M-G chaos time series, and the simulation gives staisfied result. |
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