RBF neural network implementation of fuzzy systems: Application to time series modeling

被引：0

作者：

Marcek, Milan ^{[1
,2
]}

Marcek, Dusan ^{[1
,3
]}

机构：

[1] Silesian Univ, Fac Philosophy & Sci, CZ-74601 Prague, Czech Republic

[2] MEDIS Nitra Ltd, Nitra 94901, Slovakia

[3] Univ Zilina, Fac Management Sci & Informat, Zilina 01026, Slovakia

来源：

ROUGH SETS, FUZZY SETS, DATA MINING AND GRANULAR COMPUTING, PROCEEDINGS | 2007年 / 4482卷

关键词：

probabilistic time-series models; fuzzy system; classic and soft RBF network; cloud models; granular computing;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：500 / +

页数：2

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