This work describes a highly efficient Monte Carlo sampling plan for estimating the probability that l < Λ(B) ⩽ u, the probability that a cut in Γ is critical ...

The article also describes techniques for computing confidence intervals that are valid for any sample size. Algorithms for implementing the proposed sampling.

This work describes a highly efficient Monte Carlo sampling plan for estimating the probability that l < l < Λ(B) ⩽ u, the likelihood that a cut in Γ is ...

This work describes a highly efficient Monte Carlo sampling plan for estimating the probability that l < Λ(B) ⩽ u, the probability that a cut in Γ is critical ...

这项工作描述了一个高效的蒙特卡罗抽样计划估计的概率l <Λ(B)⩽u,削减Γ至关重要的概率和l <Λ(B)⩽u的概率和降低Γ至关重要,鉴于l <Λ(B)⩽u。该方法利用了一个容易计算的概率 ...

The paper describes how a single. Monte Carlo experiment allows one to estimate the sensitivity of the probability that a particular cutset is critical, given ...

This paper proposes a discrete event algorithm for the continuous DNL problem based on flow discretizations, instead of time discretizations. These ...

This thesis describes an efficient Monte Carlo sampling plan for estimating the probability that the maximal s-t flow in a stochastic flow network greater than ...

Dec 1, 1988 · The paper describes how a single Monte Carlo experiment allows one to estimate the sensitivity of the probability that a particular cutset is ...

This algorithm is based on a combination of the Metropolis Monte Carlo method and the Hamiltonian dynamics approach. The parameterization of the inverse problem ...