Time series prediction using the parallel-structure fuzzy system

Author

Kim, Min-Soo ; Kong, Seong-Gon

Author_Institution

Dept. of Electr. Eng., Soongsil Univ., Seoul, South Korea

Volume

2

fYear

1999

fDate

22-25 Aug. 1999

Firstpage

934

Abstract

This paper presents the parallel-structure fuzzy system (PSFS) for predicting chaotic time series. The PSFS consists of multiple number of fuzzy systems connected in parallel. The fuzzy system contains Sugeno type fuzzy rules modeled using input-output training data. Each fuzzy system in the PSFS predicts the same future value based on input data with different embedding dimension and time delay. The embedding dimension is chosen optimally to have superior performance for each value of time delay. The PSFS determines the final predicted value by averaging the outputs of each fuzzy system excluding the minimum and the maximum values in order to reduce error accumulation effect.

Keywords

chaos; delays; forecasting theory; fuzzy set theory; fuzzy systems; time series; Sugeno type; chaos; embedding dimension; forecasting theory; parallel-structure fuzzy system; time delay; time series; Chaos; Delay effects; Fuzzy systems; Modems; Nonlinear systems; Prediction theory; Predictive models; Statistical analysis; Training data; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International

Conference_Location

Seoul, South Korea

ISSN

1098-7584

Print_ISBN

0-7803-5406-0

Type

conf

DOI

10.1109/FUZZY.1999.793077

Filename

793077