Data and uncertainty analysis
Data Validation: A Requirement for Enabling Data Uncertainty Analysis
... Without the presence of these channels, data accuracy bounds based on uncertainty analysis remain questionable. Also included in this presentation have been simple rules of thumb to allow ...
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Nuclear data uncertainty analysis for the Po-210 production in MYRRHA
... nuclear data for science and technology: cross sections, covariances, fission product yields and decay data, ...Nucl. Data Sheets 112, 2887 ...
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Uncertainty Analysis and Application on Smart Homes and Smart Grids: Big Data Approaches
... 4.4.1 Probabilistic Modelling with Deep Learning Deep neural networks literally refer to the multi-layer neural network models connecting multiple processing layers sequentially, to learn complex and abstract features ...
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Biological Data Analysis: Error and Uncertainty
... comparative analysis in order to demonstrate the significance of the present statistical ...the uncertainty is a quantitative estimation of errors present in a given data, where all the underlying ...
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Uncertainty and Sensitivity Analysis of Dynamic Biological Systems under Data Sparseness.
... sensitivity analysis of dynamic models. Through the bootstrap method of uncertainty analysis, we calculated confidence intervals that encapsulated true parameter values as well as the true expression ...
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Handling of uncertainty in thermodynamic data
... for uncertainty assessment has a relevant impact on the uncertainty of the PA solubility ...the uncertainty analysis used in the Simple Functions Spreadsheet follows error propagation ...
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Uncertainty analysis in the Model Web
... Web service technology designed to enable interoperability was discussed in 2.4, including those for services, and those for encoding and transferring data. Two sets of approaches for Web services were examined: ...
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Uncertainty Analysis in Statistical Matching
... of uncertainty about the model of ðX; Y; ZÞ, since the sample information provided by A and B is actually unable to discriminate among a set of plausible models for ðX; Y; ...complete data set is ...of ...
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Uncertainty Analysis Principles and Methods
... Coefficient data field. The coefficient data field can also be used to input a multiplying factor if the noise source undergoes attenuation or amplification by some external ...
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THE UNCERTAINTY ANALYSIS OF THE PIPELINE SYSTEM
... system data, the mode of functioning values, composition and physical parameters of the ...sensitivity analysis and the discussion of its results by an easy pipeline system model ...
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Transportation data analysis. Advances in data mining and uncertainty treatment
... this analysis, particular attention must be devoted to the most important factors, which represent the most significant period of the year for that ...counter’s data will allow the analyst to determine ...
187
MNGT5232 Data Analysis and Decision Making Under Uncertainty
... statistical data in the business workplace, to develop expertise in a standard set of statistical and graphical techniques that will be useful in analysing data, and to learn to apply these techniques in a ...
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WASH your data off: navigating statistical uncertainty in compositional data analysis
... binary data on households – the proportions of households that have access to WASH services – the errors cannot follow normal distributions due to the domain restrictions of proportions, limited to the range 0 to ...
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A robust correlation analysis framework for imbalanced and dichotomous data with uncertainty
... such as the case for ‘Heavy drizzle’ in which only one data point is available. The correlation 669 of ‘Heavy drizzle’ under RCAF becomes 1 while the coefficient is less than 0.1 using the 670 traditional ...
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The New Nuclear Data Sensitivity Analysis and Uncertainty Propagation Tool in NESTLE
... nuclear data—but to design and/or evaluate these reactors as transmutation systems, additional (and possibly poorly measured) nuclear data may be ...nuclear data for minor actinides Am and Cm have ...
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Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology
... and uncertainty estimation for hydrologic systems that combines a top-down, data-based mechanistic (DBM) modelling methodology; and a bottom-up, reductionist mod- elling ...rainfall-flow data, ...
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Uncertainty in geological and hydrogeological data
... with uncertainty on model structure and uncertainty in parameter variables are ...the uncertainty due to model structure is an area of novel interest, where only few operational methods have been de- ...
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Data Epistemologies / Surveillance and Uncertainty
... the data should be able to come back and surprise you about questions and patterns you had never even considered (Sterling ...for data and algorithmic ...
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Uncertainty and investment of Dutch firms: an empirical analysis using stock market data
... non-linear. Uncertainty partly results from the variability in inflation rates, as has been confirmed by the estimates presented in Section ...the uncertainty a firm is faced with mainly comes from ...
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Evaluating the quality of radiotherapy treatment plans with uncertainty using data envelopment analysis
... population-based data to give physicians a suggested target, they are very general and, consequently, unsuitable for more irregular cases such as when a large overlap between the OAR and PTV ...
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