| 随机模糊神经网络的结构学习算法研究 |
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| 引用本文： | 张骏,吕静静. 随机模糊神经网络的结构学习算法研究[J]. 计算机应用, 2005, 25(10): 2390-2391 |
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| 作者姓名： | 张骏 吕静静 |
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| 作者单位： | 西北工业大学,自动化学院,陕西,西安,710072;西北工业大学,电子与信息学院,陕西,西安,710072 |
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| 摘 要： | 基于输入层、隐层、输出层相互关系准则函数的随机模糊神经网络结构学习算法，综合考虑了输入、输出信号对隐层函数的影响。此算法的一个关键的问题是如何确定随机模糊神经网络的最佳隐层节点数。本文给出了确定最佳规则数的一般方法，并根据结果给出了相应的仿真实例。
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| 关 键 词： | 随机模糊神经网络 参数学习 隐层节点数 |
| 文章编号： | 1001-9081（2005）10-2390-02 |
| 收稿时间： | 2005-04-11 |
| 修稿时间： | 2005-04-112005-06-22 |
Structure learning method studying of stochastic fuzzy neural network |
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| ZHANG Jun,L Jing-jing. Structure learning method studying of stochastic fuzzy neural network[J]. Journal of Computer Applications, 2005, 25(10): 2390-2391 |
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| Authors: | ZHANG Jun L Jing-jing |
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| Affiliation: | 1.College of Automation,Northwestern Polytechnical University,Xi’an Shannxi 710072,China;2.School of Electronic and Information,Northwestern Polytechnical University,Xi’an Shannxi 710072,China |
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| Abstract: | Based on input layer, latent layer and output layer correlation rule, the structure learning method ot stoclaastic fuzzy neural network considered the effects on the latent layer function, which was very important for engineering applications. One key problem of this algorithm is how to get the best node number of latent layer. In this paper, a normal method to confirm the best node number was proposed. According to this theory, one simulation was presented. |
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| Keywords: | stochastic fuzzy neural network parameter learning node number of latent layer |
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