An Evolutionary Functional Link Neural Fuzzy Model for Financial Time Series Forecasting

@article{Chakravarty2011AnEF,
  title={An Evolutionary Functional Link Neural Fuzzy Model for Financial Time Series Forecasting},
  author={Sreejit Chakravarty and Pradipta Kishore Dash and V. Ravikumar Pandi and Bijaya Ketan Panigrahi},
  journal={Int. J. Appl. Evol. Comput.},
  year={2011},
  volume={2},
  pages={39-58}
}
This paper proposes a hybrid model, evolutionary functional link neural fuzzy model (EFLNF), to forecast financial time series where the parameters are optimized by two most efficient evolutionary algorithms: (a) genetic algorithm (GA) and (b) particle swarm optimization (PSO). When the periodicity is just one day, PSO produces a better result than that of GA. But the gap in the performance between them increases as periodicity increases. The convergence speed is also better in case of PSO for… 

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