Recognizing changing seasonal patterns using artificial neural networks

被引：38
|
作者：
Franses, PH
Draisma, G
机构：
[1] Econometric Institute, Erasmus University Rotterdam
来源：
JOURNAL OF ECONOMETRICS | 1997年 / 81卷 / 01期
关键词：
pattern recognition; neural networks; seasonality;
D O I：
10.1016/S0304-4076(97)00047-X
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In this paper we propose a graphical method based on an artificial neural network model to investigate how and when seasonal patterns in macroeconomic time series change over time. Neural networks are useful since the hidden layer units may become activated only in certain seasons or periods, and since this activity can be stepwise or smooth. The graphical method is based on the partial contribution of the hidden layer units to the overall fit. We apply our method to quarterly Industrial Production in France and Netherlands. (C) 1997 Elsevier Science S.A.
引用
收藏
页码：273 / 280
页数：8
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