A local linear radial basis function neural network for financial time-series forecasting

被引：0
|
作者：
Vahab Nekoukar
Mohammad Taghi Hamidi Beheshti
机构：
[1] Iran University of Science and Technology,Biomedical Engineering Group, Electrical Engineering Department
[2] Tarbiat Modares University,Control Group, Electrical Engineering Department
来源：
Applied Intelligence | 2010年 / 33卷
关键词：
Local linear radial basis function neural network; Particle swarm optimization with hunter particles algorithm; Time-series prediction; Financial forecasting;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper a Local Linear Radial Basis Function Neural Network (LLRBFN) is presented. The difference between the proposed neural network and the conventional Radial Basis Function Neural Network (RBFN) is connection weights between the hidden layer and the output layer which are replaced by a local linear model in the LLRBFN. A modified Particle Swarm Optimization (PSO) with hunter particles is introduced for training the LLRBFN. The proposed methods have been applied for prediction of financial time-series and the result shows the feasibility and effectiveness.
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页码：352 / 356
页数：4
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