RBF Network-Based Chaotic Time Series Predictionand Its Application in IRAN stock market
Hamid Yazdani1*, Ali Fallah2 ,Fatemeh Khamseh Nezhad3
1*Departmentof Electronics, Islamic Azad University, Nour Branch, Nour, Iran
2Departmentof management, Islamic Azad University, Nour Branch, Nour, Iran
3Department of Electronics, maziar University, Nour Branch, Nour, Iran
Abstract: The stock market is a chaotic dynamic system. We apply the RBF network-based chaotic time series prediction on the stock market exchange rate in Iran. We apply the RBF network and phase space reconstruction to find the optimal embedding dimension in the Iran stock market from the point view of forecasting. We find that the optimal embedding dimension is 10. Finally, we use the optimal embedding dimension to implement the prediction. [Hamid Yazdani, Ali Fallah ,Fatemeh Khamseh Nezhad. RBF Network-Based Chaotic Time Series Predictionand Its Application in IRAN stock market.Life Sci J 2013;10(7s): 326-330](ISSN:1097-8135). http://www.lifesciencesite.com. 51
Keywords: Chaotic time series, Prediction, Phase space reconstruction, RBF network, Iran stock market.