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

  • Martha Pulido
  • Patricia Melin
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 547)

Abstract

This chapter describes the design of ensemble neural networks using Particle Swarm Optimization for time series prediction with Type-1 and Type-2 Fuzzy Integration. The time series that is being considered in this work is the Mackey-Glass benchmark time series. Simulation results show that the ensemble approach produces good prediction of the Mackey-Glass time series.

Keywords

Ensemble neural networks Particle swarm Optimization Time series prediction 

Notes

Acknowledgments

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 2014

Authors and Affiliations

  1. 1.Tijuana Institute of TechnologyTijuanaMéxico

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