Time series prediction using ICA algorithms

被引：0
|
作者：
Górriz, JM [1 ]
Puntonet, CG [1 ]
Salmerón, M [1 ]
Lang, EW [1 ]
机构：
[1] Univ Cadiz, Dpto Ingenierya Sistemas & Automat Tec Elect & El, Cadiz, Spain
来源：
IDAACS'2003: PROCEEDINGS OF THE SECOND IEEE INTERNATIONAL WORKSHOP ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS | 2003年
关键词：
independent component analysis (ICA); time series analysis; neural networks; signal processing;
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：
In this paper we propose a new method for volatile time series forecasting using Independent Component Analysis (ICA) algorithms and Savitzky-Golay filtering as preprocessing, tools. The preprocessed data will be introduce in a based; radial basis functions (RBF) Artificial Neural Network (ANN) and the prediction result will be compared with the one we get without these preprocessing tools or the classical Principal Component Analysis (PCA) tool.
引用
收藏
页码：226 / 230
页数：5
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