Risk Evaluation of Slope Using Principal Component Analysis (PCA)

주성분분석을 이용한 사면의 위험성 평가

  • Jung, Soo-Jung (Dept. of Civil & Environ. Engrg., Korea Maritime Univ.) ;
  • Kim, -Yong-Soo (Research Group, Korea Infrastructure Safety&Technology Corporation) ;
  • Kim, Tae-Hyung (Dept. of Civil Engrg., Korea Maritime Univ.)
  • 정수정 (한국해양대학교 토목환경공학과) ;
  • 김용수 (한국시설안전공단 네트워크연구단) ;
  • 김태형 (한국해양대학교 토목공학과)
  • Received : 2010.09.07
  • Accepted : 2010.10.07
  • Published : 2010.10.31


To detect abnormal events in slopes, Principal Component Analysis (PCA) is applied to the slope that was collapsed during monitoring. Principal component analysis is a kind of statical methods and is called non-parametric modeling. In this analysis, principal component score indicates an abnormal behavior of slope. In an abnormal event, principal component score is relatively higher or lower compared to a normal situation so that there is a big score change in the case of abnormal. The results confirm that the abnormal events and collapses of slope were detected by using principal component analysis. It could be possible to predict quantitatively the slope behavior and abnormal events using principal component analysis.


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