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Genetic optimization of ensemble neural networks for complex time series prediction

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3 Author(s)
Pulido, M. ; Comput. Sci., Tijuana Inst. of Technol., Tijuana, Mexico ; Melin, P. ; Castillo, O.

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.

Published in:

Neural Networks (IJCNN), The 2011 International Joint Conference on

Date of Conference:

July 31 2011-Aug. 5 2011