Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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A Study on the Predictive Power Improvement of Time Series Model with Empirical Mode Decomposition Method

경험적 모드분해법을 이용한 시계열 모형의 예측력 개선에 관한 연구

  • Kim, Taereem (School of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Shin, Hongjoon (School of Civil and Environmental Engineering, Yonsei Univ.) ;
  • Nam, Woosung (K-water Seoul Metropolitan Regional Division) ;
  • Heo, Jun-Haeng (School of Civil and Environmental Engineering, Yonsei Univ.)
  • 김태림 (연세대학교 대학원 토목공학과) ;
  • 신홍준 (연세대학교 대학원 토목공학과) ;
  • 남우성 (수문기상협력센터) ;
  • 허준행 (연세대학교 공과대학 토목공학과)
  • Received : 2015.07.09
  • Accepted : 2015.10.08
  • Published : 2015.12.31
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Abstract

The analysis of hydrologic time series data is crucial for the effective management of water resources. Therefore, it has been widely used for the long-term forecasting of hydrologic variables. In tradition, time series analysis has been used to predict a time series without considering exogenous variables. However, many studies using decomposition have been widely carried out with the assumption that one data series could be mixed with several frequent factors. In this study, the empirical mode decomposition method was performed for decomposing a hydrologic time series data into several components, and each component was applied to the time series models, autoregressive moving average (ARMA). After constructing the time series models, the forecasting values are added to compare the results with traditional time series model. Finally, the forecasted estimates from ARMA model with empirical mode decomposition method showed better performance than sole traditional ARMA model indicated from comparing the root mean square errors of the two methods.

수문 시계열의 분석은 수문자료를 활용한 수자원의 효율적인 운영 및 관리에 필수적인 부분이며, 특히 장기적인 수문량 예측에 널리 활용되고 있다. 이러한 수문 시계열 분석은 전통적으로 하나의 자료계열을 하나의 요인으로 파악하여 자료를 분석하고 예측해왔지만 시계열 자료가 여러 가지 요인으로 혼합되 어 하나의 자료계열로 나타내질 수 있다는 가정 하에 각 요인들을 분해하여 분석하는 방법도 널리 연구되고 있다. 본 연구에서는 경험적 모드분해법을 이용하여 주어진 수문 시계열을 다중 성분으로 분해하고 분해된 각 요소를 시계열 모형으로 재구축한 후, 구축된 요소별 시계열 모형으로부터 예측된 값을 합하여 시계열을 예측하는 방법을 이용하였으며 이를 국내 댐 유입량에 적용한 후 그 결과를 나타내었다. 기존 시계열 모형과 경험적 모드분해법을 이용한 방법의 정확도를 비교한 결과, 기존의 시계열 모형을 이용하여 자료를 예측한 결과보다 경험적 모드분해법을 적용하여 자료를 분해한 후 시계열 자료를 예측한 결과가 주어진 시계열 자료를 더 잘 나타내는 것을 알 수 있었다.

Keywords

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