DocumentCode
3492407
Title
Genetic optimization of ensemble neural networks for complex time series prediction
Author
Pulido, M. ; Melin, P. ; Castillo, O.
Author_Institution
Comput. Sci., Tijuana Inst. of Technol., Tijuana, Mexico
fYear
2011
fDate
July 31 2011-Aug. 5 2011
Firstpage
202
Lastpage
206
Abstract
This paper describes an optimization method for ensemble neural network models with fuzzy aggregation of responses for forecasting complex time series using genetic algorithms. The time series under consideration for testing the hybrid approach is the Mackey-Glass data, and results for the optimization of type-1 fuzzy response aggregation in the ensemble neural network are presented. Simulation results show the effectiveness of the proposed approach.
Keywords
complex networks; forecasting theory; fuzzy set theory; genetic algorithms; neural nets; prediction theory; time series; Mackey-Glass data; complex time series prediction; ensemble neural network models; genetic algorithms; optimization method; type-1 fuzzy response aggregation; Fuzzy logic; Fuzzy systems; Genetic algorithms; Neural networks; Neurons; Time series analysis; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location
San Jose, CA
ISSN
2161-4393
Print_ISBN
978-1-4244-9635-8
Type
conf
DOI
10.1109/IJCNN.2011.6033222
Filename
6033222
Link To Document