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Extraction of Nonlinear Dynamical Component by Wavelet Transform in Hydro-meteorological Data

수문기상자료의 웨이블렛 변환에 의한 비선형 동역학적 성분의 추출

  • 진영훈 (동신대학교 토목공학과) ;
  • 박성천 (동신대학교 토목공학과)
  • Received : 2005.09.09
  • Accepted : 2006.05.08
  • Published : 2006.09.30

Abstract

In the present study, we applied wavelet transform to decompose the hydro-meteorological data such as precipitation and temperature into the components with different return periods with a primary objective for extraction of nonlinear dynamical component. For the transform, we used the Daubechies wavelet of order 9 ('db9') as a basis function. Also, we applied the correlation dimension analysis to determine whether or not the detail and approximation components at the respective decomposition stage with the increasing of scale in the wavelet transform reveal the nonlinear dynamical characteristics. In other words, we proposed the combined use of the wavelet transform and the correlation dimension analysis as methodology to extract the nonlinear dynamical component from the hydro-meteorological data. The derived result has shown the method proposed in the present study is suitable for the segregation and extraction of the nonlinear dynamical component which is, in general, difficult to reveal by using the raw data.

본 연구에서는 강수량 및 기온과 같은 수문기상자료의 비선형 동역학적 성분을 추출하기 위해 웨이블렛 변환을 적용하여 대상자료를 재현기간별 성분으로 분리하였다. 변환을 위한 기저함수로는 Daubechies의 9번 ('db9') 웨이블렛 함수를 사용하였다. 또한 웨이블렛 변환의 스케일의 증가에 따른 각 분리단계에서 추출된 상세성분과 근사성분이 비선형 동역학적 특성을 지니는지를 판단하기 위하여 상관차원분석을 이용하였다. 즉 수문기상자료내에 비선형 동역학적 성질을 지니는 성분을 추출하기 위한 방법론으로써 웨이블렛 변환과 상관차원분석의 결합을 제안하였으며, 도출된 결과는 일반적으로 원자료를 이용할 경우에는 파악하기 어려운 대상자료의 시간에 따른 비선형적 변화를 분리 추출하기 위해 본 연구에서 제안한 방법이 적합함을 보이고 있다.

Keywords

References

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