Evaluation of Slope Condition using Principal Component Analysis
주성분분석법을 이용한 사면 상태 평가
- Jung, Soo-Jung (Dept. of Civil & Environ. Engineering, Korea Maritime University) ;
- Kim, Tae-Hyung (Dept. of Civil Engineering, Korea Maritime University) ;
- Kang, Ki-Min (Soiltech engineering) ;
- Lee, Young-Jun (Dept. of Civil & Environ. Engineering, Korea Maritime University)
- Published : 2010.09.09
Estimating condition of geotechnical structures are difficult because of nonlinear time dependency and seasonal effects. Measuring data of structure failure is highly variable in time and space, and a unique approach cannot be defined to model structure 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. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, this method is advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured.