doi: 10.7763/IJIET.2013.V3.271
Time Series Prediction Using Fuzzy Cerebellar Model Articulation Controller with Symbiotic Particle Swarm Optimization
Chin-Ling Lee
,
Cheng-Jian Lin
Abstract
In this paper, a fuzzy cerebellar model articulation controller (FCMAC) model with learning ability is proposed for solving the time series prediction problem. An efficient learning algorithm, called symbiotic particle swarm optimization (SPSO), combined symbiotic evolution and modified particle swarm optimization for tuning parameters of the FCMAC. Simulation results show that the converging speed and root mean square error (RMS) of the proposed method has a better performance than those of other methods.
Keywords
- Cerebellar model articulation controller
- fuzzy set
- particle swarm optimization
- symbiotic evolution
- time series
- prediction
How to Cite
Chin-Ling Lee and Cheng-Jian Lin, "Time Series Prediction Using Fuzzy Cerebellar Model Articulation Controller with Symbiotic Particle Swarm Optimization," International Journal of Information and Education Technology, vol. 3, no. 2, pp. 235-239, 2013. https://doi.org/10.7763/IJIET.2013.V3.271
Copyright & License
Copyright © 2013 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).