Results 291 to 300 of about 8,187,354 (351)

Estimating Quantile Sensitivities

Operations Research, 2009
Quantiles of a random performance serve as important alternatives to the usual expected value. They are used in the financial industry as measures of risk and in the service industry as measures of service quality. To manage the quantile of a performance, we need to know how changes in the input parameters affect the output quantiles, which are called
openaire   +3 more sources

Probability sensitivity estimation of linear stochastic finite element models applying Line Sampling

Structural Safety, 2019
This paper presents a framework for probability sensitivity estimation of a class of problems involving linear stochastic finite element models. The sensitivity measure consists of the derivative of the failure probability with respect to the statistics ...
M. Valdebenito, H. B. Hernández, H. Jensen   +2 more
semanticscholar   +1 more source

Global reliability sensitivity estimation based on failure samples

Structural Safety, 2019
Global reliability sensitivity analysis (RSA) can help to assess the effects of input random variables X on the probability of failure Pr(F) of an engineering system.
Luyi Li, Luyi Li, I. Papaioannou, D. Štraub   +3 more
semanticscholar   +1 more source

Novel voltage-to-power sensitivity estimation for phasor measurement unit-unobservable distribution networks based on network equivalent

Applied Energy, 2019
The access and application of phasor measurement units (PMUs) in distribution networks highly improve the system observability and further enhance the performance of operation control and energy management.
Hongzhi Su, Chengshan Wang, Peng Li, Peng Li, Zhelin Liu, Jianzhong Wu   +5 more
semanticscholar   +1 more source

Rainfall erosivity in Slovenia: Sensitivity estimation and trend detection

Environmental Research, 2018
Slovenia is one of the EU countries with the largest values and largest amounts of variability in rainfall erosivity, with maximum annual values exceeding 10,000 MJ mm ha‐1 h‐1 yr‐1.
M. Petek, M. Mikoš, N. Bezak
semanticscholar   +1 more source

Sensitivity analysis of M-estimates

Annals of the Institute of Statistical Mathematics, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Sensitivity of the EOQ Model to Parameter Estimates

Operations Research, 1988
The Economic Order Quantity (EOQ) model for independent demand is well known to be somewhat insensitive to the choice of order quantity. The cost goes up as the square root of the ratio of the actual order quantity to that of the optimal order quantity. The question arises as to how sensitive this cost is to parameter estimates. This paper extends the
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Risk-sensitive estimation and a differential game

IEEE Transactions on Automatic Control, 1994
Summary: A large deviation result is employed to solve the state estimation problem of a continuous time Gauss-Markov system with an exponential cost. The exponential cost is the expected value of an exponential function of the state estimation-error.
Ravi N. Banavar, Jason L. Speyer
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Adaptive Model Predictive Fault-Tolerant Control for Four-Wheel Independent Steering Vehicles with Sensitivity Estimation

International journal of automotive technology, 2023
Sechan Oh, Taejun Song, Min Jun Kim, K. Oh   +3 more
semanticscholar   +1 more source

Estimating Sensitivity to Input Model Variance

2019 Winter Simulation Conference (WSC), 2019
Simple question: How sensitive is your simulation output to the variance of your simulation input models? Unfortunately, the answer is not simple because the variance of many standard parametric input distributions can achieve the same change in multiple ways as a function of the parameters. In this paper we propose a family of output-mean-with-respect-
Wendy Xi Jiang, Barry L. Nelson, L. Jeff Hong   +2 more
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