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 67 for “"Model Error"”.
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Optimal Bayesian experimental design in the presence of model error
… experimental design with simulation-based models, with the goal of maximizing information gain in targeted subsets of model parameters, particularly in situations where experiments are costly. Our framework employs a Bayesian statistical setting, which naturally incorporates heterogeneous …
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Capturing the impact of model error on structural dynamic analysis during design evolution
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2001.
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A First Complete Approach to Address Model Error in Computational Turbulent Heat Transfer
… of turbulent heat flux has plagued the CFD modeling community for decades. A systemic dearth of adequate data has forced modelers to heavily rely on intuition and ad hoc reasoning to justify modeling choices. Many turbulence modelers believe that error in CFD temperature prediction stems …
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Techniques to account for and reduce model inadequacy in ensemble-based filters
A technique for the accounting for parametric model error in the Ensemble Kalman Filter (EnKF) is investigated within the framework of Additive Error Approximation (AEA). The AEA needs an estimate of the model error covariance structure. The state-dependent model error structure is the sensitivity …
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Make Some Noise: Methods for Generating Data from Imperfect Factor Models
… studies involving covariance structure models (e.g., the common factor model) have increasingly recognized the importance of incorporating error due to model misfit in simulated data. Incorporating this model error acknowledges that all models are literally false, and no covariance …
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Detecting and Addressing Model Structural Error in Forecasting for Model Predictive Control
… an understanding of the nonlinear behavior of models, chaos, and individual challenges predictability. A systemic approach is presented for improving model predictive strategies in uncertainties in dynamical system forecasting for decision-making. In this thesis, as a first step, different …
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Financial Portfolio Risk Management: Model Risk, Robustness and Rebalancing Error
… management. While more and more complicated models are proposed and implemented as research advances, they all inevitably rely on imperfect assumptions and estimates. This dissertation aims to investigate the gap between complicated theoretical modelling and practice. We mainly focus on two …
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Measurement covariance-constrained estimation for poorly modeled dynamic systems
… dynamic systems which accounts for system model errors in a much more rigorous manner than Kalman filter-smoother type methods. The Kalman filter-smoother type methods, which currently dominate post-experiment estimation practice, treat model errors via “process noise", which essentially …
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A dynamical system approach to data assimilation in chaotic models
… Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the …
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Error-free message transmission in the universal composability framework
This thesis introduces models for error-prone communication channels and functionalities for error-free communication in the Universal Composability framework. Realizing these functionalities enables protocols to make use of cryptographic error-correcting schemes which are more powerful than …
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Quantifying the Sensitivity of Land-Surface Models to Hydrodynamic Stress Limitations on Transpiration
… and carbon uptake rates. Current land-surface models couple stomata conductance and soil moisture through empirical relationships. This approach does not take advantage of recent advances in our understanding of water flow and storage in trees or of tree and canopy structure. The lack of …
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Adaptive error estimation in linearized ocean general circulation models
… used in oceanography. The statistics of the model and measurement errors need to be specified a priori. In this study we address the problem of estimating model and measurement error statistics from observations. We start by testing the Myers and Tapley (1976, MT) method of adaptive error …
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Adaptive error estimation in linearized ocean general circulation models
… used in oceanography. The statistics of the model and measurement errors need to be specified a priori. In this study we address the problem of estimating model and measurement error statistics from observations. We start by testing the Myers and Tapley (1976, MT) method of adaptive error …
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Applications of Neutrino Physics
… oscillation experiments on reactor neutrino flux model. We fit the largest reactor neutrino flux model error, weak magnetism, using data from experiments. We use reactor burn-up simulations in combination with a reactor neutrino flux model to demonstrate the capability of a neutrino detector to …
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A time-varying subsidence parameterization for the atmospheric boundary layer
… on a one-dimensional coupled land-atmosphere model. Measurements of large-scale divergence in the ABL are scarce and often marred by error, providing the motivation to model this important physical process and estimate its values from indirect but related observations. Constant …
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A Study of Mathematical Modeling of Remaining Useful Life, Assessment, and Prognostics & Health Management (PHM)
<p>This research centers on mathematical modeling of remaining useful life (RUL) and its assessment of a device or system. Remaining useful life has always been an essential part of reliability theory. It has also been equally important in various other fields such as actuarial science, engineering …
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What are the odds? A preliminary test of a theoretical model of sports team effectiveness
… test of the Sports Team Effectiveness (STE) Model developed by Devine, Lindsey, and Wolfarth in 2017. The purpose of this study was to examine the extent to which several variables help explain winning in professional basketball. The value of the STE model in predicting the winner of …
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An analysis of posynomial MOSFET models using genetic algorithms and visualization
… Geometric programming, which uses posynomial models of MOSFET parameters, represents one such tool. Genetic algorithms have been used to evolve posynomial models for geometric programs, with a reasonable mean error when modeling MOSFET parameters. By visualizing MOSFET data using two …
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Evaluation of GLEAMS considering parameter uncertainty
… from the GLEAMS nonpoint source pollution model. Assessment of both the procedure and model was made by comparing absolute and relative predictions made with both probabilistic and deterministic procedures. Field data used came from a study of pesticide fate and transport in both no-till …
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Quantification of Uncertainties for Conducting Partially Non-ergodic Probabilistic Seismic Hazard Analysis
… and use this database to develop a predictive model for the Fourier Amplitude Spectra of ground motions. The ground motion model (GMM) residuals are used to investigate the stability of site terms across different tectonic regimes. We observe that empirical site terms are stable across …
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