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Evaluating Epistemic Uncertainty from Random Variables at the Terminal Branches of a Logic Tree
We present solutions for a combined probability density function computed as the weighted sum of individual probability density functions at the terminal branches of a logic tree. Logic trees are commonly utilized to quantify epistemic uncertainty in system analysis and can be computationally expensive when many branches and variables are included. The information provided herein can reduce those computational demands. We first derive closed-form expressions for the first two moments of the combined probability density function and subsequently derive expressions for the probability density function in cases where the mean value of the individuals is either normally or uniformly distributed and the variance is constant.
Evaluating Epistemic Uncertainty from Random Variables at the Terminal Branches of a Logic Tree
We present solutions for a combined probability density function computed as the weighted sum of individual probability density functions at the terminal branches of a logic tree. Logic trees are commonly utilized to quantify epistemic uncertainty in system analysis and can be computationally expensive when many branches and variables are included. The information provided herein can reduce those computational demands. We first derive closed-form expressions for the first two moments of the combined probability density function and subsequently derive expressions for the probability density function in cases where the mean value of the individuals is either normally or uniformly distributed and the variance is constant.
Evaluating Epistemic Uncertainty from Random Variables at the Terminal Branches of a Logic Tree
ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng.
Brandenberg, Scott J. (Autor:in) / Pretell, Renmin (Autor:in)
01.09.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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