An application of the LHS technique in the field of rock slope stability assessment will then be discussed. The development of the LHS technique will first be described and then compared with the Monte Carlo sampling technique. Each row and column have unique selection. This has been successfully applied to rock slope stability analyses concerning plane and wedge failure and has been found to represent the original data more closely than could Monte Carlo sample sets of the same size. Latin hypercube sampling, motivated by latin squares, the hypercube is in N-D. LHS, in essence, is a constrained randomisation sampling scheme which is sensitive to the extreme values of the data range. However computation time can be substantial if significant sampling errors are to be avoided.Īn alternative approach has been developed which uses the Latin Hypercube Sampling (LHS) approach to the same algorithms. Such analyses have been succesfully solved using a Monte Carlo Sampling approach based on well-established deterministic algorithms. as the penalty associated with observing 1 out of 2 whereas the other metrics would weight these. A probabilistic approach to slope stability analysis allows the observed natural variability of many parameters to be taken into consideration. sampling (LHS) locations (Minasny and McBratney 2006).
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