Variability, Uncertainty and Confidence in Model Predictions
How To Model The Variability And Uncertainty Of Photovoltaic Generation
... 95% confidence interval) of the predicted dis- tribution using method 3, the worst-case assumption for geo- graphic autocorrelation of volatility ...97.5% confidence bound between 0 and 1 times for 27 ...
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Bootstrap Optical Flow Confidence and Uncertainty Measure
... 1.2. Proposed method Our uncertainty measure is based on bootstrap resam- pling [12]. The basic idea is as follows: If we had multiple realizations of the given OF estimation problem, such as mul- tiple recordings ...
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Uncertainty quantification of flood mitigation predictions and implications for interventions
... the predictions of com- puter models are inherently uncertain, and it is currently un- known to what extent that uncertainty affects predictions of the effect of flood mitigation ...the ...
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Uncertainty propagation from the cell transmission traffic flow model to emission predictions: a data-driven approach
... highest variability has been observed for the supply parameters of CTM models in comparison to the demand ...CTM model outputs have been observed to be road network specific and thus the final estimated ...
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Improving Back Translation with Uncertainty based Confidence Estimation
... the confidence of NMT model predictions based on model ...sentence-level confidence measures based on uncertainty, it is possible for back-translation to better cope with noise ...
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Uncertainty and variability in chemical exposure assessment for the workplace
... that uncertainty and variability in the model predictions are often ...of uncertainty in chemical-specific input data and variability in physiological ...PBPK model are ...
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Quantifying uncertainty on sediment loads using bootstrap confidence intervals
... concentration predictions are obtained with errors smaller than 15 % (Horowitz, ...the uncertainty is stated to be con- ...the variability in the concentration ...calculating uncertainty on ...
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Quantification of Variability and Uncertainty in Emission Factors and Emission Inventories
... quarter, confidence intervals for both were calculated using an ...percent confidence intervals for the mean. Similarly, 95 percent confidence intervals for the variance were estimated based upon the ...
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Bug Triaging with High Confidence Predictions
... High confidence prediction ensures that the model only triages bugs when the statistical confi- dence for a developer is ...High confidence pre- dictions also improve the accuracy for Eclipse ...
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The communication and influence of confidence and uncertainty
... the model is most likely to work, namely those where both individuals have common interests and want to exchange information ...the model will not work as well, and as with other heuristics, the ...
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Climate model variability leads to uncertain predictions of the future abundance of stream macroinvertebrates
... the variability among GCMs and ...streamflow predictions 33 and their selection are a major source of uncertainty in climate change impact studies 18 , the magnitude by which they influence abundance ...
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Predictions shape confidence in the right inferior frontal gyrus
... (full/diverted), confidence (confident/guess), and expectation-response congruence ...second-level model, which used an uncorrected peak threshold of p ⬍ ...
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The impact of rheological uncertainty on dynamic topography predictions
... topography predictions derived from mantle con- vection models are generally larger by a factor of 2 (more significant at the very-large scales) than estimates from resid- ual topography (Hoggard et ...rheological ...
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Uncertainty, Validation and Sensitivity Analyses of the OpenSim Muscle Model for Pre- and Post-flight Strength Predictions
... the model will consist of simplified models of the OpenSim muscle model parameters as a function of time in space, based on spaceflight data – Later versions of the DAP muscle model will be based ...
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Probabilistic methods for addressing uncertainty and variability in biological models: application to a toxicOkinetic model
... distribution. As seen in our results, it is important to use a sufficiently large sample size so that the observations contain an adequate representation of the population. The results for the probability-based estimation ...
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Quantifying uncertainty in climate-driven disease risk predictions
... This may be illustrated by an extreme example. Consider a forecast system issuing equally distributed probabilities of an event, between 0 and 100%. Now say that across the forecast-observation pairs, every time the ...
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Considering rating curve uncertainty in water level predictions
... hydraulic model, (ii) uncertainty about its parameters and (iii) measurement errors (Di Bal- dassarre et ...the uncertainty of cal- ibration data is an ongoing issue, considerable progress has been ...
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A Simple, Coherent Framework for Partitioning Uncertainty in Climate Predictions
... partitioning uncertainty in multimodel climate ensembles is pre- ...scenario uncertainty, model uncertainty, and internal ...quantify uncertainty related to model–scenario ...
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Quantifying uncertainty in the estimation of probability distributions with confidence bands
... 3.2 Simulated Data and Computational Results We now describe the simulated population density data used in the inverse problem for the estimation of growth rate distributions for the mosquitofish model. We began ...
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Dealing with uncertainty in agent-based models for short-term predictions
... the model parameters until the model satisfies some predetermined ...also uncertainty about the bus operations that comes from the lack of information regarding the current system ...any model ...
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