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IEEE Transactions on Power Systems, 2023
This letter proposes a new robust data-driven sparse voltage sensitivity estimation approach for large-scale distribution systems with PVs. It has a high statistical efficiency to mitigate the impacts of PV stochasticity and unknown measurement noise ...
Yingqi Liang +3 more
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This letter proposes a new robust data-driven sparse voltage sensitivity estimation approach for large-scale distribution systems with PVs. It has a high statistical efficiency to mitigate the impacts of PV stochasticity and unknown measurement noise ...
Yingqi Liang +3 more
semanticscholar +1 more source
, 2021
This contribution focuses on evaluating the sensitivity associated with first excursion probabilities of linear structural systems subject to stochastic Gaussian loading.
M. Valdebenito +3 more
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This contribution focuses on evaluating the sensitivity associated with first excursion probabilities of linear structural systems subject to stochastic Gaussian loading.
M. Valdebenito +3 more
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A sensitive estimator for crosscorrelograms
Biological Cybernetics, 1990The best established method for finding interactions between extracellularly recorded neurons is the crosscorrelation technique. The method is simple and useful, but it has some drawbacks. One of them is its limited sensitivity to weak interactions, which are common in the mammalian cerebral cortex.
I, Nelken, E, Vaadia
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Sensitivity estimation for Gaussian systems
European Journal of Operational Research, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bernd Heidergott +2 more
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An Autonomous Charge Controller for Electric Vehicles Using Online Sensitivity Estimation
IEEE transactions on industry applications, 2020Despite their sustainable benefits, large-scale adoption of electric vehicles (EVs) into the distribution system is challenging. Uncontrolled charging of EVs could increase voltage violations, system power losses, and feeder overloads.
Saifullah Shafiq, A. Al-Awami
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The sensitivity of estimates of regression to the mean
Accident Analysis & Prevention, 2009Estimations of the effectiveness of remedial treatments in road safety analysis are frequently bedevilled by the problem of regression to the mean (RTM). The number of accidents x observed at a site in the "before" period is a "noisy" quantity: x is Poisson distributed about an (unknown) true mean m for that site, so that x = m + e.
Mike, Maher, Linda, Mountain
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Quantile Sensitivity Estimation
2009Quantiles are important performance characteristics that have been adopted in many areas for measuring the quality of service. Recently, sensitivity analysis of quantiles has attracted quite some attention. Sensitivity analysis of quantiles is particularly challenging as quantiles cannot be expressed as the expected value of some sample performance ...
Heidergott, B.F., Volk-Makarewicz, W.M.
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Reliability sensitivity estimation with sequential importance sampling
Structural Safety, 2018In applications of reliability analysis, the sensitivity of the probability of failure to design parameters is often crucial for decision-making. A common sensitivity measure is the partial derivative of the probability of failure with respect to the ...
I. Papaioannou, K. Breitung, D. Štraub
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New Theory and Faster Computations for Subspace-Based Sensitivity Map Estimation in Multichannel MRI
IEEE Transactions on Medical Imaging, 2023Sensitivity map estimation is important in many multichannel MRI applications. Subspace-based sensitivity map estimation methods like ESPIRiT are popular and perform well, though can be computationally expensive and their theoretical principles can be ...
Rodrigo A. Lobos +2 more
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