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