| 摘要: |
| 给出了一种新型的模糊神经网络模型.该模型不需要领域专家的知识进行指导，而是通过对样本竞争分类产生模糊规则.每类样本对应于一条模糊规则，每条模糊规则的后件部分为一个对本类样本进行过学习训练的神经网络.文章以模糊神经网络在时间序列分析中的应用为例，通过与传统的时间序列分析方法以及前向神经网络方法的对比，说明了新型模糊神经网络的有效性. |
| 关键词: 模糊神经网络,模糊系统,样本,竞争分类,时间序列分析. |
| DOI： |
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| 基金项目:本文研究得到国家自然科学基金和国家教育部符号计算与知识工程开放实验室资金资助. |
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| Fuzzy Neural Network and Its Applications in Time Series Analysis |
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ZHOU Chun-guang,ZHANG Bing,LIANG Yan-chun,HU Cheng-quan,CHANG Di
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| Abstract: |
| A new fuzzy neural network model is presented in this paper. In the new model, the fuzzy rules are generated through the competitive classification of samples without the aid of domain experts. One class of samples forms a fuzzy rule. The consequent part of each fuzzy rule is a feed forward neural network trained using the corresponding class of samples. The application of the fuzzy neural network to the analysis of time series is taken as an example to demonstrate the effectiveness of the fuzzy neural network through the comparison with the conventional analysis of time series and neural network methods. |
| Key words: Fuzzy neural network, fuzzy system, samples, competitive classification, time series analysis. |
