An improved boosting scheme based ensemble of Fuzzy Neural Networks for nonlinear time series prediction

@article{Dong2014AnIB,
  title={An improved boosting scheme based ensemble of Fuzzy Neural Networks for nonlinear time series prediction},
  author={Yilin Dong and Jianhua Zhang},
  journal={2014 International Joint Conference on Neural Networks (IJCNN)},
  year={2014},
  pages={157-164}
}
This paper proposed a Modified AdaBoostRT (AdaBoost Regression and Threshold) algorithm based on Fuzzy Neural Networks (FNNs) and its application to the accurate prediction of complex nonlinear time-series. The algorithm is validated by using four typical time-series data, namely Lorenz, Mackey-Glass, Sunspot and Dow Jones Indices data. The performance comparison of the proposed method and several existing approaches is also performed to show its advantages for nonlinear time series prediction… CONTINUE READING

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SHOWING 1-10 OF 21 REFERENCES

A new approach for time series prediction using ensembles of ANFIS models

J. Soto Melin, O. Castillo, J. Soria
  • Expert Systems with Applications
  • 2012

Chaotic Time Series Prediction Based on Radial Basis Function Network

  • Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)
  • 2007