标题 |
Comparison of Selection Method of a Membership Function for Fuzzy Neural Networks
模糊神经网络隶属函数选取方法的比较
相关领域
人工神经网络
选择(遗传算法)
模糊逻辑
计算机科学
人工智能
隶属函数
功能(生物学)
机器学习
数学
数据挖掘
模糊集
生物
进化生物学
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其它 | Fuzzy neural networks are learning machine that realize the parameters of a fuzzy system (i.e., fuzzy sets, fuzzy rules) by exploiting approximation techniques from neural networks. In this paper, we tend to illustrate a general methodology, based on statistical analysis of the training data, for the choice of fuzzy membership functions to be utilized in reference to fuzzy neural networks. Fuzzy neural networks give for the extraction of fuzzy rules for from artificial neural network architectures. First, the technique is represented and so illustrated utilizing two experimental examinations for determining the alternate approach of the fuzzy neural network. |
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