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RBF Neural Network Implementation of Fuzzy Systems: Application to Time Series Modeling

机译:模糊系统的RBF神经网络实现:在时间序列建模中的应用

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At first, we discuss the basic structure of the fuzzy system as a simple yet powerful fuzzy modeling technique. Neural networks and fuzzy logic models are based on very similar underlying mathematics. The similarity between RBF networks and fuzzy models is noted in detail. Then, we propose the extension of RBF neural networks by the cloud model. Time series approximation and prediction by applying RBF neural networks or fuzzy models and comparisons between the various types of RBF networks and statistical models are discussed at length.
机译:首先,我们将模糊系统的基本结构作为一种简单而强大的模糊建模技术进行讨论。神经网络和模糊逻辑模型基于非常相似的基础数学。详细指出了RBF网络与模糊模型之间的相似性。然后,我们提出了云模型对RBF神经网络的扩展。详细讨论了通过应用RBF神经网络或模糊模型进行时间序列逼近和预测,以及各种类型的RBF网络与统计模型之间的比较。

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