Chaotic time series prediction using PSFS2

Author

Kim, Min-Soo ; Lee, Hae-Soo ; You, Chi-Hyoung ; Chung, Chan-Soo

Author_Institution

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

Volume

4

fYear

2002

fDate

5-7 Aug. 2002

Firstpage

2358

Abstract

Presents a generalized parallel structure fuzzy system (PSFS2) for prediction of chaotic time series like sunspot number data. The PSFS2 consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS2 predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedded dimension determines the number of inputs of each component fuzzy system and a time delay decides the interval of inputs of the time series. According to the embedding dimension and the time delay, the component fuzzy system takes various input output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems in order to reduce the error accumulation effect.

Keywords

forecasting theory; fuzzy set theory; fuzzy systems; mean square error methods; nonparametric statistics; time series; chaotic time series prediction; embedding dimension; error accumulation effect; generalised parallel-structure fuzzy system; nonparametric approach; subtractive clustering; sunspot number data; time delay; Chaos; Delay effects; Fuzzy systems;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE 2002. Proceedings of the 41st SICE Annual Conference

Print_ISBN

0-7803-7631-5

Type

conf

DOI

10.1109/SICE.2002.1195777

Filename

1195777