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A linguistic information feed-back-based dynamical fuzzy system (LIFBDFS) with learning algorithm

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Abstract

In this study, the linguistic information feed-back-based dynamical fuzzy system (LIFBDFS) proposed earlier by the authors is first introduced. The principles of α-level sets and backpropagation through time approach are also briefly discussed. We next employ these two methods to derive an explicit learning algorithm for the feedback parameters of the LIFBDFS. With this training algorithm, our LIFBDFS indeed becomes a potential candidate in solving real-time modeling and prediction problems.

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Acknowledgments

This research work was funded by the Academy of Finland under Grant 201353. The authors would like to thank the anonymous reviewers for their insightful comments and constructive suggestions that have improved the paper.

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Authors and Affiliations

  1. Institute of Intelligent Power Electronics, Helsinki University of Technology, Otakaari 5 A, 02150, Espoo, Finland

    X. Z. Gao, S. J. Ovaska & X. Wang

Authors
  1. X. Z. Gao
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  2. S. J. Ovaska
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  3. X. Wang
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Correspondence to X. Z. Gao.

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Gao, X.Z., Ovaska, S.J. & Wang, X. A linguistic information feed-back-based dynamical fuzzy system (LIFBDFS) with learning algorithm. Neural Comput & Applic 18, 321–329 (2009). https://doi.org/10.1007/s00521-008-0183-5

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  • DOI: https://doi.org/10.1007/s00521-008-0183-5

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