Comparative evaluation of genetic algorithm and backpropagation for training neural networks
Information Sciences—Informatics and Computer Science: An International Journal
Financial Time Series Data Forecasting by Wavelet and TSK Fuzzy Rule Based System
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Multiple-Period Modified Fuzzy Time-Series for Forecasting TAIEX
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Type-2 Fuzzy Logic: Theory and Applications
GRC '07 Proceedings of the 2007 IEEE International Conference on Granular Computing
Hybrid Learning Algorithm for Interval Type-2 Fuzzy Neural Networks
GRC '07 Proceedings of the 2007 IEEE International Conference on Granular Computing
PEITS '08 Proceedings of the 2008 Workshop on Power Electronics and Intelligent Transportation System
Hierarchical Type-2 Neuro-Fuzzy BSP Model
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Forecasting Stock Price Using a Genetic Fuzzy Neural Network
ICCSIT '08 Proceedings of the 2008 International Conference on Computer Science and Information Technology
A type-2 fuzzy rule-based expert system model for stock price analysis
Expert Systems with Applications: An International Journal
Chaotic Time Series Forecasting Base on Fuzzy Adaptive PSO for Feedforward Neural Network Training
ICYCS '08 Proceedings of the 2008 The 9th International Conference for Young Computer Scientists
Development and performance evaluation of FLANN based model for forecasting of stock markets
Expert Systems with Applications: An International Journal
Surveying stock market forecasting techniques - Part II: Soft computing methods
Expert Systems with Applications: An International Journal
Forecasting TAIFEX based on fuzzy time series and particle swarm optimization
Expert Systems with Applications: An International Journal
Evolutionary fuzzy neural networks for hybrid financial prediction
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
Interval Type-2 Fuzzy Logic Systems Made Simple
IEEE Transactions on Fuzzy Systems
A Self-Evolving Interval Type-2 Fuzzy Neural Network With Online Structure and Parameter Learning
IEEE Transactions on Fuzzy Systems
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This paper presents an integrated functional link interval type-2 fuzzy neural system (FLIT2FNS) for predicting the stock market indices. The hybrid model uses a TSK (Takagi-Sugano-Kang) type fuzzy rule base that employs type-2 fuzzy sets in the antecedent parts and the outputs from the Functional Link Artificial Neural Network (FLANN) in the consequent parts. Two other approaches, namely the integrated FLANN and type-1 fuzzy logic system and Local Linear Wavelet Neural Network (LLWNN) are also presented for a comparative study. Backpropagation and particle swarm optimization (PSO) learning algorithms have been used independently to optimize the parameters of all the forecasting models. To test the model performance, three well known stock market indices like the Standard's & Poor's 500 (S&P 500), Bombay stock exchange (BSE), and Dow Jones industrial average (DJIA) are used. The mean absolute percentage error (MAPE) and root mean square error (RMSE) are used to find out the performance of all the three models. Finally, it is observed that out of three methods, FLIT2FNS performs the best irrespective of the time horizons spanning from 1 day to 1 month.