A hybrid evolutionary dynamic neural network for stock market trend analysis and prediction using unscented Kalman filter
- 1 June 2014
- journal article
- Published by Elsevier BV in Applied Soft Computing
- Vol. 19, 41-56
- https://doi.org/10.1016/j.asoc.2014.01.039
Abstract
No abstract availableThis publication has 25 references indexed in Scilit:
- A Decision tree- Rough set Hybrid System for Stock Market Trend PredictionInternational Journal of Computer Applications, 2010
- Forecasting TAIFEX based on fuzzy time series and particle swarm optimizationExpert Systems with Applications, 2010
- Development and performance evaluation of FLANN based model for forecasting of stock marketsExpert Systems with Applications, 2009
- A type-2 fuzzy rule-based expert system model for stock price analysisExpert Systems with Applications, 2009
- Time-series prediction using a local linear wavelet neural networkNeurocomputing, 2006
- A comparison of global, recurrent and smoothed-piecewise neural models for Istanbul stock exchange (ISE) predictionPattern Recognition Letters, 2005
- FLANN Based Forecasting of S&P 500 IndexInformation Technology Journal, 2005
- A hybrid genetic-neural architecture for stock indexes forecastingInformation Sciences, 2005
- Optimal partition algorithm of the RBF neural network and its application to financial time series forecastingNeural Computing & Applications, 2004
- Neural networks in financial engineering: a study in methodologyIEEE Transactions on Neural Networks, 1997