Application of Radial Basis Functions in Neural Networks for Prognosis of Economic Parameters

被引：0

作者：

Dudnik, Olga V. ^{[2
]}

Bidyuk, Pyetr I. ^{[1
]}

机构：

[1] Natl. Tech. University of Ukraine, Kyiv Polytechnical Institute, Ukraine

[2] Inst. of Applied Systems Analysis, Natl. Academy of Sciences of Ukraine, Min. of Educ. and Science of Ukraine, Kyiv, Ukraine

来源：

Journal of Automation and Information Sciences | 2003年 / 35卷 / 1-4期

关键词：

Computational methods - Data processing - Error analysis - Expert systems - Extrapolation - Kalman filtering - Knowledge acquisition - Mathematical transformations - Parameter estimation - Polynomials - Probability - Problem solving - Radial basis function networks - Real time systems - Transfer functions - Vectors;

D O I：

10.1615/jautomatinfscien.v35.i4.50

中图分类号：

学科分类号：

摘要：

The specific architecture of a feedforward neural network is described. Using example of two real time series, namely exchange rates of Ukrainian hryvna to US dollar and that of Ukrainian hryvna to Russian rouble for the second half of 1997, we demonstrate possibility of prognosis using neural network, whose structure contains radial nodes. The results of operation of a model of such architecture are presented and comparison of its possibilities with those of a classic model of multilayer perception (MLP model) is performed.

引用

页码：39 / 45

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