Prediction of Sunspot Number Time Series using the Parallel-Structure Fuzzy Systems

병렬구조 퍼지시스템을 이용한 태양흑점 시계열 데이터의 예측

  • 김민수 (세종-우주항공연구소 연구교수) ;
  • 정찬수 (숭실대 공대 전기공학과)
  • Published : 2005.06.01

Abstract

Sunspots are dark areas that grow and decay on the lowest level of the sun that is visible from the Earth. Shot-term predictions of solar activity are essential to help plan missions and to design satellites that will survive for their useful lifetimes. This paper presents a parallel-structure fuzzy system(PSFS) for prediction of sunspot number time series. The PSFS consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedding 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 error accumulation effect.

Keywords

References

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