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Predicting chaotic time series with fuzzy if-then rules

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2 Author(s)
J. -S. R. Jang ; Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Berkeley, CA, USA ; C. -T. Sun

The authors continue work on a previously proposed ANFIS (adaptive-network-based fuzzy inference system) architecture, with emphasis on the applications to time series prediction. They show how to model the Mackey-Glass chaotic time series with 16 fuzzy if-then rules. The performance obtained outperforms various standard statistical approaches and artificial neural network modeling methods reported in the literature. Other potential applications of ANFIS are also suggested

Published in:

Fuzzy Systems, 1993., Second IEEE International Conference on

Date of Conference: