Ensemble Neural Network Optimization Using the Particle Swarm Algorithm with Type-1 and Type-2 Fuzzy Integration for Time Series Prediction

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 574)

Abstract

This paper shows the optimization of ensemble neural networks using the Particle Swarm algorithm for time series prediction with Type-1 and Type-2 Fuzzy Integration. The time series that is being considered in this paper is the Dow Jones Time Series. Simulation results show that the ensemble approach produces good prediction of the Dow Jones time series.

Keywords

Ensemble neural networks Particle swarm Optimization Time series prediction 

Notes

Acknowledgment

We would like to express our gratitude to the CONACYT, Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Tijuana Institute of TechnologyTijuanaMéxico

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