DOI QR코드

DOI QR Code

HCBKA 기반 오차 보정형 TSK 퍼지 예측시스템 설계

Design of HCBKA-Based TSK Fuzzy Prediction System with Error Compensation

  • 방영근 (강원대 전기전자공학과) ;
  • 이철희 (강원대 전기전자공학부)
  • 투고 : 2010.01.29
  • 심사 : 2010.05.13
  • 발행 : 2010.06.01

초록

To improve prediction quality of a nonlinear prediction system, the system's capability for uncertainty of nonlinear data should be satisfactory. This paper presents a TSK fuzzy prediction system that can consider and deal with the uncertainty of nonlinear data sufficiently. In the design procedures of the proposed system, HCBKA(Hierarchical Correlationship-Based K-means clustering Algorithm) was used to generate the accurate fuzzy rule base that can control output according to input efficiently, and the first-order difference method was applied to reflect various characteristics of the nonlinear data. Also, multiple prediction systems were designed to analyze the prediction tendencies of each difference data generated by the difference method. In addition, to enhance the prediction quality of the proposed system, an error compensation method was proposed and it compensated the prediction error of the systems suitably. Finally, the prediction performance of the proposed system was verified by simulating two typical time series examples.

키워드

참고문헌

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