DocumentCode
638778
Title
Optimization of ensemble neural networks with type-2 fuzzy response integration for predicting the Mackey-Glass time series
Author
Pulido, Martha ; Melin, Patricia ; Castillo, Oscar
Author_Institution
Div. of Grad. Studies & Res., Tijuana Inst. of Technol., Tijuana, Mexico
fYear
2013
fDate
12-14 Aug. 2013
Firstpage
16
Lastpage
21
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 a method of optimization for the ensemble model in this case of study. The time series that is being considered is the Mackey-Glass benchmark. Simulation results show that the ensemble approach produces good prediction of the Mackey-Glass time series.
Keywords
fuzzy logic; genetic algorithms; neural nets; time series; Mackey-Glass time series; ensemble neural network; genetic algorithm; type-1 fuzzy logic; type-2 fuzzy logic; type-2 fuzzy response integration; Fuzzy systems; Genetics; Noise; Ensemble; Genetic Algorithms; Neural Networks; Optimization; Time Series Prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Nature and Biologically Inspired Computing (NaBIC), 2013 World Congress on
Conference_Location
Fargo, ND
Print_ISBN
978-1-4799-1414-2
Type
conf
DOI
10.1109/NaBIC.2013.6617857
Filename
6617857
Link To Document