Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 52 for “"Data uncertainty"”.
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A Monte Carlo framework for nuclear data uncertainty propagation via the windowed multipole formalism
… framework has been developed that calculates the uncertainty in calculated quantities, such as K[subscript eff], reactivity coefficients, multigroup cross sections, and reaction rate ratios, that arise due to uncertainties in the underlying nuclear data. This framework relies on first order …
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Nuclear Computations under Uncertainty New methods to infer and propagate nuclear data uncertainty across Monte Carlo simulations
… to efficiently infer and propagate nuclear data uncertainty across Monte Carlo simulations of nuclear technologies. The main contributions come in two areas: 1. novel statistical methods and machine learning algorithms (Embedded Monte Carlo); 2. new mathematical parametrizations of the …
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Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions
… problems: determining the accuracy of input data and assumptions, the limitations of historical validation, and uncertainty in parameter requirements for unit commitment models used for validation. Two aspects of the first problem are explored. The first concerns the uncertainty surrounding …
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Advances in Bayesian Machine Learning: From Uncertainty to Decision Making
Bayesian uncertainty quantification is the key element to many machine learning applications. To this end, approximate inference algorithms are developed to perform inference at a relatively low cost. Despite the recent advancements of scaling approximate inference to “big model $\times$ big data” …
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Steady models of Arctic shelf-basin exchange
… an inverse box model. The model accounts for data uncertainty in the estimates, and quantifies the solution uncertainty. Other features include resolution of the two-basin Arctic hydrographic structure two-way shelf-basin exchange in the surface mixed layer, the capacity for shelfbreak …
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Aircraft stability and departure prediction using Eigenvalue Sensitivity analysis
… returning both quantitative and qualitative data regarding the stability of the airplane at a static reference condition. SADATES not only supplies the analyst with information describing where and when an aircraft is likely to depart, but also information about the departure characteristics, …
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Reservoir yield estimates with consideration of uncertainty in used data in Illinois
… of associated uncertainties in used data. Errors exist in inflow, reservoir capacity, evaporation and precipitation data and contribute to the overall uncertainty in reservoir yield estimates. Before combining optimization with Monte Carlo simulation, errors of each data category are …
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Robust portfolio optimization
… sensitive outcome by the small changes in the data. Ben-Tal and Nemirovski [3] therefore introduced the robust counterpart approach of the optimization problem to provide more conservative results. And on the ground of their work, Schottle [26] furthermore proposed the local robust counterpart …
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Robust optimization of linear optimization problems and an approximation approach to solve robust Knapsack Problem
… the robust KP exactly is difficult due to this data uncertainty and combinatorial structure of the problem. In this research, a polynomial-time algorithm is proposed to approximately obtain a near optimal solution for the robust KP with a provable quality. The quality is described by an error …
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Robust optimization for network-based resource allocation problems under uncertainty
… resource allocation problems under uncertainty, with specific focus on the class of problems referred to as multi-commodity flow problems with time-windows. These problems are at the core of many network-based resource allocation problems. Inherent data uncertainty in the problem …
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Cost Risk Management for a Small to Medium-sized Enterprise in the Cladding Industry
… and implementation of this approach. Controlling data transfer between systems produces a knowledge-based model, allowing cladding industry designers and estimators to take more accurate decisions, with the objective of reducing risk and improving company profitability. This model, with the …
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Development and Evaluation of Contrail Models
… and relative magnitudes of errors due to weather data uncertainty and errors due to modeling assumptions have not been extensively studied, despite many studies relying on the CoCiP model and the ERA5 weather data for their analyses. This thesis addresses these gaps. The APCEMM model is optimized …
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Essays on Agricultural Greenhouse Gas Emission Footprints: Accounting, Bias, and Trade Policy
… greenhouse gas emissions, yet substantial uncertainty persists in measuring emissions intensities of agricultural production and the carbon footprint of international trade at the commodity-country level. These uncertainties arise from fragmented emissions accounting frameworks. At the same …
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Mitigating airport congestion : market mechanisms and airline response models
… model is efficient and was found to be robust to data uncertainty in our experimental simulations.
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Stormwater Monitoring: Evaluation of Uncertainty due to Inadequate Temporal Sampling and Applications for Engineering Education
… A methodology is presented to (i) evaluate the uncertainty due to inadequate temporal sampling of stormflow data, and (ii) develop equations using regional regression analysis that can be used to select a stormflow sampling frequency of a watershed. A case study demonstrates how the proposed …
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Using electrical resistivity tomography to calibrate seawater intrusion models along the Alabama Gulf Coast
… be limited by the availability of hydrological data, uncertainty in these results can be substantially reduced through the integration of field geophysical measurements. Field measurements employing electrical resistivity tomography (ERT) were utilized to calibrate a density-dependent …
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Power system real-time thermal rating estimation
… system, such as reducing measurements points, data uncertainty and communication failure. An extensive validation allowed a quantification of the performance of the algorithm developed, building the necessary confidence for a practical application of the system developed.
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On the Certification of Deep Learning-based Dynamical System Identification
… in the classical neural network-based aleatoric uncertainty estimators. We identify overestimation issues in existing variance attenuation methods and propose a novel denoising-based approach that provides more accurate estimates of data uncertainty. This method not only applies to regression …
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SCALE AND SOURCE OF GEOSPATIAL DATA FOR WILDFIRE RISK ASSESSMENTS: COMPARING NATIONAL DATA WITH LOCAL DATA IN THE DESCHUTES NATIONAL FOREST
Widespread use of geospatial data in environmental decision-making tools such as wildfire risk models has called attention to questions of availability, quality, and currency of input data layers. As wildfires are modeled with growing confidence and knowledge of how resources respond to fire is …
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