Optimization of type-2 fuzzy integration in ensemble neural networks for predicting the US Dolar/MX pesos time series

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.