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A neuro-fuzzy method for predicting the chaotic time series

Hu Yu-Xia Gao Jin-Feng

A neuro-fuzzy method for predicting the chaotic time series

Hu Yu-Xia, Gao Jin-Feng
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  • Abstract views:  3268
  • PDF Downloads:  922
  • Cited By: 0
Publishing process
  • Received Date:  18 November 2004
  • Accepted Date:  14 May 2005
  • Published Online:  20 November 2005

A neuro-fuzzy method for predicting the chaotic time series

  • 1. 郑州大学电气工程学院,郑州 450002

Abstract: A neuro-fuzzy approach based on a novel hybrid learning method is presented, which can generate the best fuzzy rule set automatically from the desired input-output data pairs only and can give the initial neuro-fuzzy system and the initial parameters of fuzzy membership functions. Then the parameters of fuzzy membership functions and the weights can be easily tuned by employing neural network's self-learning techniques. This approach reduces the rule matching time and accelerates the speed of the fuzzy logic referencing and improves the adaptability of the neuro-fuzzy system. Using the proposed neuro-fuzzy system and the learning algorithms we simulated the prediction of the Lorenz chaotic time series, the results demonstrate the effectiveness of the chaotic time series prediction approach.

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