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Applied Intelligence

, Volume 33, Issue 3, pp 352–356 | Cite as

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

  • Vahab Nekoukar
  • Mohammad Taghi Hamidi Beheshti
Article

Abstract

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.

Keywords

Local linear radial basis function neural network Particle swarm optimization with hunter particles algorithm Time-series prediction Financial forecasting 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Vahab Nekoukar
    • 1
  • Mohammad Taghi Hamidi Beheshti
    • 2
  1. 1.Biomedical Engineering Group, Electrical Engineering DepartmentIran University of Science and TechnologyTehranIran
  2. 2.Control Group, Electrical Engineering DepartmentTarbiat Modares UniversityTehranIran

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