DocumentCode :
635877
Title :
Optimization of type-2 fuzzy integration in ensemble neural networks for predicting the US Dolar/MX pesos time series
Author :
Pulido, Martha ; Melin, Patricia ; Castillo, Oscar
Author_Institution :
Tijuana Inst. of Technol., Tijuana, Mexico
fYear :
2013
fDate :
24-28 June 2013
Firstpage :
1508
Lastpage :
1512
Abstract :
This paper describes the optimization of an ensemble neural network with fuzzy integration of responses based on type-1 and type-2 fuzzy logic. Genetic algorithms are used as method of optimization in this case. The time series that is being considered for the ensemble is the US Dollar/MX Peso exchange rate. Simulation results show that the ensemble approach produces good prediction of the exchange rate US Dollar/MX Peso.
Keywords :
economic forecasting; exchange rates; fuzzy logic; fuzzy set theory; genetic algorithms; neural nets; prediction theory; time series; US Dolar/MX pesos time series; US Dollar/MX Peso exchange rate prediction; ensemble approach; ensemble neural network; genetic algorithms; optimization; type-1 fuzzy logic; type-2 fuzzy integration; type-2 fuzzy logic; Fuzzy logic; Fuzzy systems; Genetic algorithms; Neural networks; Optimization; Predictive models; Time series analysis; Ensemble Neural Networks; Genetic Algorithms; Optimization; Time Series Prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint
Conference_Location :
Edmonton, AB
Type :
conf
DOI :
10.1109/IFSA-NAFIPS.2013.6608626
Filename :
6608626
Link To Document :
بازگشت