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A new multi-point univariate decomposition method is presented for structural reliability analysis involving multiple most probable points (MPPs).
The Ditlevsen's bounds of system probability of failure are also computed by taking into account the correlations between three failure modes, which is evaluated using the direction cosines of the tangent planes at the most probable points of failure.
Since the imbedded fastPMA needs the gradient calculations and the initial guesses of the most probable points (MPPs), their proposed algorithm would encounter difficulties in dealing with non-differentiable constraints and the effectiveness could be degraded significantly as the initial guesses are far from the true MPPs.
By applying phylogenetic methods of ancestral state reconstruction, we can reconstruct the probable points of origin on the eukaryote phylogeny of the various proteins.
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A new simulation method presented by authors to approximate the failure probability and most probable point.
First, the most probable focal element (MPFE), an important concept as the most probable point (MPP) in probability-theory-based reliability analysis, is searched using a uniformity approach.
In this paper, a new simulation method for approximating the probability of failure and the most probable point of failure is proposed.
This paper presents a new univariate method employing the most probable point as the reference point for predicting failure probability of structural and mechanical systems subject to random loads, material properties, and geometry.
The idea behind the DNA projects is that analysts can look for telltale sequences in African-Americans' genes that also appear in the current populations of various African regions, and thus link the Americans to their probable point of origin.
In these circumstances, it is difficult to determine the most probable point for the laser line.
The method, called Most Probable Point System Simulation (MPPSS) is simple, and numerically-based.
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