Feed-forward and recurrent neural networks in signal prediction

被引：0

作者：

Prochazka, Ales ^{[1
]}

Pavelka, Ales ^{[1
]}

机构：

[1] Prague Inst Chem Technol, Dept Comp & Control Engn, CR-16628 Prague 6, Czech Republic

来源：

ICCC 2007: 5TH IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL CYBERNETICS, PROCEEDINGS | 2007年

关键词：

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：

The paper is devoted to time series prediction using linear, perceptron and Elman neural networks of the selected architecture and proposed pattern structure. Signal wavelet de-noising in the preprocessing stage of signal modelling is discussed as well. The main part of the paper is devoted to the comparison of different models of time series prediction. The proposed algorithm is applied to processing of the real data sets representing gas consumption in the Czech Republic observed with the given sampling period.

引用

页码：93 / 96

页数：4

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