Time series prediction with ensemble models applied to the CATS benchmark

被引：15

作者：

Wichard, Joerg D.

Ogorzalek, Maciej

机构：

[1] Inst Mol Pharmacol, Mol Modelling Grp, D-13125 Berlin, Germany

[2] AGH Univ Sci & Technol, Dept Elect Engn, PL-30059 Krakow, Poland

来源：

NEUROCOMPUTING | 2007年 / 70卷 / 13-15期

基金：

日本学术振兴会;

关键词：

neural networks; ensemble methods; time series prediction;

D O I：

10.1016/j.neucom.2005.12.136

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We describe the use of ensemble methods to build models for time series prediction. Our approach extends the classical ensemble methods for neural networks by using several different model architectures. We further suggest an iterated prediction procedure to select the final ensemble members. (C) 2007 Elsevier B.V. All rights reserved.

引用

页码：2371 / 2378

页数：8

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