Predicting chaotic time series with fuzzy if-then rules

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