Time-series forecasting using flexible neural tree model

被引:208
作者
Chen, YH
Yang, B
Dong, JW
Abraham, A
机构
[1] Jinan Univ, Sch Informat Sci & Engn, Jinan 250022, Peoples R China
[2] Chung Ang Univ, Sch Engn & Comp Sci, Seoul 156756, South Korea
基金
中国国家自然科学基金;
关键词
flexible neural tree model; probabilistic incremental program evolution; simulated annealing; time-series forecasting;
D O I
10.1016/j.ins.2004.10.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Time-series forecasting is an important research and application area. Much effort has been devoted over the past several decades to develop and improve the time-series forecasting models. This paper introduces a new time-series forecasting model based on the flexible neural tree (FNT). The FNT model is generated initially as a flexible multi-layer feed-forward neural network and evolved using ail evolutionary procedure. Very often it is a difficult task to select the proper input variables or time-lags for constructing a time-series model. Our research demonstrates that the FNT model is capable of handing the task automatically. The performance and effectiveness of the proposed method are evaluated using time series prediction problems and compared with those of related methods. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:219 / 235
页数:17
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