Prediction of Chaotic Time Series Using Fuzzy Identification

퍼지 식별을 이용한 카오스 시계열 데이터 예측

  • 고재호 (광운대학교 제어계측공학과) ;
  • 방성윤 (광운대학교 제어계측공학과) ;
  • 도병조 (광운대학교 제어계측공학과) ;
  • 배영철 (산업 정보 기술원) ;
  • 임화영 (광운대학교 제어계측공학과)
  • Published : 1997.07.21

Abstract

In this paper, fuzzy logic system equipped with the back-propagation training algorithm as identifiers for nonlinear dynamic systems is described. To improve its performance, Jacob's delta-bar -delta rule is adapted in adjusting stepsize ${\alpha}$, and only y and ${\alpha}$ updating algorithm is suggested. In identifying and predicting the chaotic time series, suggested method is better than Li-Xin Wang's method,[1]

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