Robust Short Term Prediction using Combination of Linear Regression and Modified Probabilistic Neural Network Model

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

In many business applications, accurate short term prediction is vital for survival. Many different techniques have been applied to model business data in order to produce accurate prediction. Artificial neural network (ANN) have shown excellent potential however it requires better extrapolation capacity in order to provide reliable prediction. In this paper, a combination of piecewise linear regression model in parallel with general regression neural network is introduced for short term financial prediction. The experiment shows that the proposed hybrid model achieves superior prediction performance compared to the conventional prediction techniques such as the MultiLayer Perceptron (MLP) or Volterra series based prediction.

Original languageEnglish
Pages2478-2481
Number of pages4
Publication statusPublished - 2003
Externally publishedYes
EventInternational Joint Conference on Neural Networks 2003 - Portland, OR, United States
Duration: 20 Jul 200324 Jul 2003

Conference

ConferenceInternational Joint Conference on Neural Networks 2003
Country/TerritoryUnited States
CityPortland, OR
Period20/07/0324/07/03

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