The Transactions of the Korean Institute of Electrical Engineers A (대한전기학회논문지:전력기술부문A)

The Korean Institute of Electrical Engineers (대한전기학회)
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RBF Network Structure for Prediction of Non-linear, Non-stationary Time Series

비선형, 비정상 시계열 예측을 위한 RBF(Radial Basis Function) 회로망 구조

  • Kim, Sang-Hwan (Dept.of Electric Engineering, Graduate School of Inha University) ;
  • Lee, Jong-Ho (Dept.of Electronics Engineering, Inha University)
  • 김상환 (인하대 대학원 전기공학 졸업 석사) ;
  • 이종호 (인하대 전기전자컴퓨터공학부)
  • Published : 1999.02.01
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Abstract

In this paper, a modified RBF(Radial Basis Function) network structure is suggested for the prediction of a time-series with non-linear, non-stationary characteristics. Coventional RBF network predicting time series by using past outputs sense the trajectory of the time series and react when there exists strong relation between input and hidden activation function's RBF center. But this response is highly sensitive to level and trend of time serieses. In order to overcome such dependencies, hidden activation functions are modified to react to the increments of input variable and multiplied by increment(or dectement) for prediction. When the suggested structure is applied to prediction of Macyey-Glass chaotic time series, Lorenz equation, and Rossler equation, improved performances are obtained.

Keywords

References

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