DocumentCode :
230088
Title :
Optimization of ensemble neural networks with fuzzy integration using the particle swarm algorithm for the US Dollar/MX time series prediction
Author :
Pulido, Martha ; Melin, Patricia ; Castillo, Oscar
Author_Institution :
Tijuana Inst. of Technol., Tijuana, Mexico
fYear :
2014
fDate :
24-26 June 2014
Firstpage :
1
Lastpage :
7
Abstract :
This paper describes the design with Particle Swarm Optimization of a neural network ensemble with type-1 and type-2 fuzzy integration of responses. The proposed ensemble neural network approach is tested with the problem of time series prediction. The time series that is being considered for testing the hybrid approach is the US/Dollar MX time series. Simulation results show that the ensemble neural network approach produces good prediction of the Dollar time series.
Keywords :
exchange rates; financial data processing; fuzzy reasoning; fuzzy set theory; neural nets; particle swarm optimisation; time series; US Dollar/MX time series prediction; ensemble neural network optimization; hybrid approach; particle swarm algorithm; type-1 fuzzy integration; type-2 fuzzy integration; Biological neural networks; Fuzzy systems; Neurons; Optimization; Particle swarm optimization; Prediction algorithms; Time series analysis; Ensemble Neural Networks; Optimization; Particle Optimization Swarm; Time Series Prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Norbert Wiener in the 21st Century (21CW), 2014 IEEE Conference on
Conference_Location :
Boston, MA
Type :
conf
DOI :
10.1109/NORBERT.2014.6893877
Filename :
6893877
Link To Document :
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