한국지반공학회:학술대회논문집 (Proceedings of the Korean Geotechical Society Conference)
- 한국지반공학회 2010년도 춘계 학술발표회
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- Pages.1358-1365
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- 2010
주성분 분석기법을 적용한 사면 계측데이터 평가
Slope Displacement Data Estimation using Principal Component Analysis
- Jung, Soo-Jung (Korea Infrastructure Safety &, Technology Corporation) ;
- Kim, Yong-Soo (Korea Infrastructure Safety &, Technology Corporation) ;
- Ahn, Sang-Ro (Korea Infrastructure Safety &, Technology Corporation)
- 발행 : 2010.03.25
초록
Estimating condition of slope is difficult because of nonlinear time dependency and seasonal effects, which affect the displacements. Displacements and displacement patterns of landslides are highly variable in time and space, and a unique approach cannot be defined to model landslide movements. Characteristics of movements are obtained by using a statistical method called Principal Component Analysis(PCA). The PCA is a non-parametric method to separate unknown, statistically uncorrelated source processes from observed mixed processes. In the non-parametric approaches, no physical assumptions of target systems are required. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, non-parametric approaches are advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured. Non-parametric approaches are consequently more flexible in modeling than parametric approaches. This method is expected to be a useful tool for the slope management of and alarm systems.