Predicting chaotic time series with fuzzy if-then rules

Jyh Shing Roger*, Chuen-Tsai Sun

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

49 Scopus citations

Abstract

This paper presents the continued work of a previously proposed ANFIS (Adaptive-Network-based Fuzzy Inference System) architecture, with emphasis on the applications to time series prediction. We explain how to model the Mackey-Glass chaotic time series with 16 fuzzy if-then rules. The performance we obtained outperforms various standard statistical approaches and artificial neural network modeling reported in the literature. Other potential applications of ANFIS are also suggested.

Original languageEnglish
Title of host publication1993 IEEE International Conference on Fuzzy Systems
PublisherPubl by IEEE
Pages1079-1084
Number of pages6
ISBN (Print)0780306155
DOIs
StatePublished - 1 Jan 1993
EventSecond IEEE International Conference on Fuzzy Systems - San Francisco, CA, USA
Duration: 28 Mar 19931 Apr 1993

Publication series

Name1993 IEEE International Conference on Fuzzy Systems

Conference

ConferenceSecond IEEE International Conference on Fuzzy Systems
CitySan Francisco, CA, USA
Period28/03/931/04/93

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    Roger, J. S., & Sun, C-T. (1993). Predicting chaotic time series with fuzzy if-then rules. In 1993 IEEE International Conference on Fuzzy Systems (pp. 1079-1084). (1993 IEEE International Conference on Fuzzy Systems). Publ by IEEE. https://doi.org/10.1109/FUZZY.1993.327364