subject:(Parameter uncertainty)

Colorado State University

1. Sabatine, Shaina M. Evaluation of parameter and model uncertainty in simple applications of a 1D sediment transport model.

Degree: MS(M.S.), Civil and Environmental Engineering, 2011, Colorado State University

URL: http://hdl.handle.net/10217/70825

► This paper aims to quantify parameter and model uncertainty in simulations from a 1D sediment transport model using two methods from Bayesian statistics. The first… (more)

Subjects/Keywords: Bayesian model averaging; sediment transport uncertainty; parameter uncertainty; parameter optimization; model uncertainty

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APA (6^th Edition):

Sabatine, S. M. (2011). Evaluation of parameter and model uncertainty in simple applications of a 1D sediment transport model. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/70825

Chicago Manual of Style (16^th Edition):

Sabatine, Shaina M. “Evaluation of parameter and model uncertainty in simple applications of a 1D sediment transport model.” 2011. Masters Thesis, Colorado State University. Accessed January 19, 2021. http://hdl.handle.net/10217/70825.

MLA Handbook (7^th Edition):

Sabatine, Shaina M. “Evaluation of parameter and model uncertainty in simple applications of a 1D sediment transport model.” 2011. Web. 19 Jan 2021.

Vancouver:

Sabatine SM. Evaluation of parameter and model uncertainty in simple applications of a 1D sediment transport model. [Internet] [Masters thesis]. Colorado State University; 2011. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10217/70825.

Council of Science Editors:

Sabatine SM. Evaluation of parameter and model uncertainty in simple applications of a 1D sediment transport model. [Masters Thesis]. Colorado State University; 2011. Available from: http://hdl.handle.net/10217/70825

Delft University of Technology

2. Lin, Yuhan (author). Improving hydrological model performance using storm- dependent parameters.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:5885cd50-b3a8-46c1-b85c-062d67556fa9

► Calibration and model prediction is always affected by uncertainty in the forcing data, response data and structural error in the model. The storm-dependent parameters are… (more)

▼ Calibration and model prediction is always affected by uncertainty in the forcing data, response data and structural error in the model. The storm-dependent parameters are believed to be able to capture these errors and improve model prediction. The goal of this research will be to further investigate and develop the storm-based approach and compare it to more traditional approaches, including the use of static (time- invariant) parameters and the use of GLUE to capture model errors. The hypothesis in this paper is the ran- dom variation of storm-dependent parameters can capture the model error and improve the prediction. The storm-based method will apply a sensitivity analysis to identify the storm-dependent parameters that are most likely to vary by storms. The variation of storm-dependent parameters will give large changes in model performance which is measured by Nash–Sutcliffe efficiency. In the storm-based method, parameters will be calibrated storm by storm in the calibration period. Then in the validation period, streamflow will still be predicted storm by storm through picking each parameter set from the calibrated parameter sets. Besides, the effect of dryness and the optimal threshold for identifying the storm epochs on the model performance will also be explored in the storm-based method. The results obtained by the storm-based method will be compared with the method using static parameters and GLUE method. Six case studies calibrating a con- ceptual rainfall-runoff model with for parameters with daily data illustrate the improvement of prediction obtained by the storm-based method for dry basins. The extent of variation of storm-dependent parameters is very random in each case which indicates there is error in the model. Moreover, the extent of variation of storm-dependent parameters has no relation with initial water storage, rainfall characteristic and basin characteristics. Although the parameters cannot be predicted deterministically, they can be predicted prob- abilistically with the histogram or fitted distribution for the calibrated parameter sets in the future work. By making storm-dependent parameters vary with storms and other parameters constant, the storm-based method performs better for drier basins while worse for wetter basins compared to GLUE method and tradi- tional method. The logscore value obtained in storm-based method(e.g. -0.68 for one of the dry basin A) is larger than those obtained in the traditional method (e.g. -1.23 for basin A) and GLUE method (e.g. -0.67 for basin A). Additionally, the RMSE values for total flow obtained in the storm-based method are all smaller than those obtained in the traditional method, and GLUE method for dry basins. This suggests the storm-based method is more applicable for dry basins and this method should be better developed for wet basins. What is more, the extent of variation of storm-dependent parameters has no relation with basin characteristics but the mean and variation of the storm-dependent parameters can be obtained. Hence the extent of… Advisors/Committee Members: Schoups, G.H.W. (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: storm-dependent parameter; CRR model; model uncertainty

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APA (6^th Edition):

Lin, Y. (. (2020). Improving hydrological model performance using storm- dependent parameters. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5885cd50-b3a8-46c1-b85c-062d67556fa9

Chicago Manual of Style (16^th Edition):

Lin, Yuhan (author). “Improving hydrological model performance using storm- dependent parameters.” 2020. Masters Thesis, Delft University of Technology. Accessed January 19, 2021. http://resolver.tudelft.nl/uuid:5885cd50-b3a8-46c1-b85c-062d67556fa9.

MLA Handbook (7^th Edition):

Lin, Yuhan (author). “Improving hydrological model performance using storm- dependent parameters.” 2020. Web. 19 Jan 2021.

Vancouver:

Lin Y(. Improving hydrological model performance using storm- dependent parameters. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Jan 19]. Available from: http://resolver.tudelft.nl/uuid:5885cd50-b3a8-46c1-b85c-062d67556fa9.

Council of Science Editors:

Lin Y(. Improving hydrological model performance using storm- dependent parameters. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:5885cd50-b3a8-46c1-b85c-062d67556fa9

University of Alberta

3. Hosseini, Amir Hossein. Probabilistic modeling of natural attenuation of petroleum hydrocarbons.

Degree: PhD, Department of Civil and Environmental Engineering, 2009, University of Alberta

URL: https://era.library.ualberta.ca/files/44558d91x

► Natural attenuation refers to the observed reduction in contaminant concentration via natural processes as contaminants migrate from the source into environmental media. Assessment of the… (more)

▼ Natural attenuation refers to the observed reduction in contaminant concentration via natural processes as contaminants migrate from the source into environmental media. Assessment of the dimensions of contaminant plumes and prediction of their fate requires predictions of the rate of dissolution of contaminants from residual non-aqueous-phase liquids (NAPLs) into the aquifer and the rate of contaminant removal through biodegradation. The available techniques to estimate these parameters do not characterize their confidence intervals by accounting for their relationships to uncertainty in source geometry and hydraulic conductivity distribution. The central idea in this thesis is to develop a flexible modeling approach for characterization of uncertainty in residual NAPL dissolution rate and first-order biodegradation rate by tailoring the estimation of these parameters to distributions of uncertainty in source size and hydraulic conductivity field. The first development in this thesis is related to a distance function approach that characterizes the uncertainty in the areal limits of the source zones. Implementation of the approach for a given monitoring well arrangement results in a unique uncertainty band that meets the requirements of unbiasedness and fairness of the calibrated probabilities. The second development in this thesis is related to a probabilistic model for characterization of uncertainty in the 3D localized distribution of residual NAPL in a real site. A categorical variable is defined based on the available CPT-UVIF data, while secondary data based on soil texture and groundwater table elevation are also incorporated into the model. A cross-validation study shows the importance of incorporation of secondary data in improving the prediction of contaminated and uncontaminated locations. The third development in this thesis is related to the implementation of a Monte Carlo type inverse modeling to develop a screening model used to characterize the confidence intervals in the NAPL dissolution rate and first-order biodegradation rate. The development of the model is based on sequential self-calibration approach, distance-function approach and a gradient-based optimization. It is shown that tailoring the estimation of the transport parameters to joint realizations of source geometry and transmissivity field can effectively reduce the uncertainties in the predicted state variables.

Subjects/Keywords: inverse modeling; geostatistics; parameter uncertainty; contaminant transport; parameter estimation; natural attenuation

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APA (6^th Edition):

Hosseini, A. H. (2009). Probabilistic modeling of natural attenuation of petroleum hydrocarbons. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/44558d91x

Chicago Manual of Style (16^th Edition):

Hosseini, Amir Hossein. “Probabilistic modeling of natural attenuation of petroleum hydrocarbons.” 2009. Doctoral Dissertation, University of Alberta. Accessed January 19, 2021. https://era.library.ualberta.ca/files/44558d91x.

MLA Handbook (7^th Edition):

Hosseini, Amir Hossein. “Probabilistic modeling of natural attenuation of petroleum hydrocarbons.” 2009. Web. 19 Jan 2021.

Vancouver:

Hosseini AH. Probabilistic modeling of natural attenuation of petroleum hydrocarbons. [Internet] [Doctoral dissertation]. University of Alberta; 2009. [cited 2021 Jan 19]. Available from: https://era.library.ualberta.ca/files/44558d91x.

Council of Science Editors:

Hosseini AH. Probabilistic modeling of natural attenuation of petroleum hydrocarbons. [Doctoral Dissertation]. University of Alberta; 2009. Available from: https://era.library.ualberta.ca/files/44558d91x

University of Illinois – Urbana-Champaign

4. Ji, Xiang. Impact of uncertain input on parameter estimation in groundwater model.

Degree: MS, 0106, 2012, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/31967

► Description of the aquifer characteristics accurately and efficiently is the most commonly encountered and probably the most challenging aspect of groundwater modeling. In the context… (more)

▼ Description of the aquifer characteristics accurately and efficiently is the most commonly encountered and probably the most challenging aspect of groundwater modeling. In the context of groundwater modeling, although many studies have focused on parameter estimation problems, these issues are far from being solved. When important hydrogeological parameters like transmissivity and storativity are estimated using regression-based inverse methods, it is assumed that all other parameters and quantities are known. In particular, it is assumed that pumping rates are known. This will not be a valid assumption for groundwater basins subject to intensive irrigation pumping since farmers are normally not required to report their pumping amounts to any government regulatory office. In this thesis, we study the impact of uncertainty in pumping upon estimation of hydrogeological parameters. We use three typical simplified groundwater models to test the impact of uncertain pumping on the parameter estimation and we use statistical methods to assess the results. The uncertainty analysis using the Matlab Regression Toolbox of the Thiem and Theis model shows that the impact of uncertain drawdown is less than the impact of uncertain pumping. The uncertainty analysis using PEST for a more complex model with a partially penetrating stream shows that the stream depletion cannot be used to estimate the transmissivity and the drawdown cannot be used to estimate the riverbed conductivity. The biases of estimated parameters commonly exist and they increase with the increasing uncertainty of model input. The impact of uncertain pumping rate is also more significant than the impact of uncertain observations. Finally, we estimate the pumping uncertainty in a real case by studying the data from the Republican River Compact Administration (RRCA) model. In this unusual case, we have actual metered pumping data, as well as an assumed pumping rate that was used in the RRCA model. For the Upper Natural Resources District of Nebraska, the error (uncertainty) in pumping rates approximately follows a Gaussian distribution. But the pumping rate used in the model is underestimating the actual pumping data. Advisors/Committee Members: Valocchi, Albert J. (advisor).

Subjects/Keywords: Thiem; Theis; groundwater; parameter estimation; Parameter ESTimation (PEST); uncertainty

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APA (6^th Edition):

Ji, X. (2012). Impact of uncertain input on parameter estimation in groundwater model. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/31967

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Ji, Xiang. “Impact of uncertain input on parameter estimation in groundwater model.” 2012. Thesis, University of Illinois – Urbana-Champaign. Accessed January 19, 2021. http://hdl.handle.net/2142/31967.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Ji, Xiang. “Impact of uncertain input on parameter estimation in groundwater model.” 2012. Web. 19 Jan 2021.

Vancouver:

Ji X. Impact of uncertain input on parameter estimation in groundwater model. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2012. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/2142/31967.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ji X. Impact of uncertain input on parameter estimation in groundwater model. [Thesis]. University of Illinois – Urbana-Champaign; 2012. Available from: http://hdl.handle.net/2142/31967

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Colorado State University

5. Yen, Haw. Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences.

Degree: PhD, Civil and Environmental Engineering, 2012, Colorado State University

URL: http://hdl.handle.net/10217/71604

► Simulation modeling is arguably one of the most powerful scientific tools available to address questions, assess alternatives, and support decision making for environmental management. Watershed… (more)

▼ Simulation modeling is arguably one of the most powerful scientific tools available to address questions, assess alternatives, and support decision making for environmental management. Watershed models are used to describe and understand hydrologic and water quality responses of land and water systems under prevailing and projected conditions. Since the promulgation of the Clean Water Act of 1972 in the United States, models are increasingly used to evaluate potential impacts of mitigation strategies and support policy instruments for pollution control such as the Total Maximum Daily Load (TMDL) program. Generation, fate, and transport of water and contaminants within watershed systems comprise a highly complex network of interactions. It is difficult, if not impossible, to capture all important processes within a modeling framework. Although critical natural processes and management actions can be resolved at varying spatial and temporal scales, simulation models will always remain an approximation of the real system. As a result, the use of models with limited knowledge of the system and model structure is fraught with uncertainty. Wresting environmental decisions from model applications must consider factors that could conspire against credible model outcomes. The main goal of this study is to develop a novel Bayesian-based computational framework for characterization and incorporation of uncertainties from forcing inputs, model parameters, model structures, and measured responses in the parameter estimation process for multisite multiple-response watershed modeling. Specifically, the following objectives are defined: (i) to evaluate the effectiveness and efficiency of different computational strategies in sampling the model parameter space; (ii) to examine the role of measured responses at various locations in the stream network as well as intra-watershed processes in enhancing the model performance credibility; (iii) to facilitate combining predictions from competing model structures; and (iv) to develop a statistically rigorous procedure for incorporation of errors from input, parameter, structural and measurement sources in the parameter estimation process. The proposed framework was applied for simulating streamflow and total nitrogen at multiple locations within a 248 square kilometer watershed in the Midwestern United States using the Soil and Water Assessment Tool (SWAT). Results underlined the importance of simultaneous treatment of all sources of uncertainty for parameter estimation. In particular, it became evident that incorporation of input uncertainties was critical for determination of model structure for runoff generation and also representation of intra-watershed processes such as denitrification rate and dominant pathways for transport of nitrate within the system. The computational framework developed in this study can be implemented to establish credibility for modeling watershed processes. More importantly, the framework can reveal how collection of data from different responses at… Advisors/Committee Members: Arabi, Mazdak (advisor), Fontane, Darrell G. (committee member), Hoag, Dana L. (committee member), Loftis, Jim C. (committee member).

Subjects/Keywords: parameter estimation; uncertainty analysis; predictive uncertainty; Bayesian inferences; optimization; watershed calibration

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Yen, H. (2012). Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/71604

Chicago Manual of Style (16^th Edition):

Yen, Haw. “Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences.” 2012. Doctoral Dissertation, Colorado State University. Accessed January 19, 2021. http://hdl.handle.net/10217/71604.

MLA Handbook (7^th Edition):

Yen, Haw. “Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences.” 2012. Web. 19 Jan 2021.

Vancouver:

Yen H. Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences. [Internet] [Doctoral dissertation]. Colorado State University; 2012. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10217/71604.

Council of Science Editors:

Yen H. Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences. [Doctoral Dissertation]. Colorado State University; 2012. Available from: http://hdl.handle.net/10217/71604

University of Arizona

6. Sun, Jin. Conquering Variability for Robust and Low Power Designs .

Degree: 2011, University of Arizona

URL: http://hdl.handle.net/10150/145458

► As device feature sizes shrink to nano-scale, continuous technology scaling has led to a large increase in parameter variability during semiconductor manufacturing process. According to… (more)

Subjects/Keywords: Circuit Verification; On-line Self-tuning; Parameter Variations; Uncertainty Importance; Uncertainty Importance; Robust Optimization

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APA (6^th Edition):

Sun, J. (2011). Conquering Variability for Robust and Low Power Designs . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/145458

Chicago Manual of Style (16^th Edition):

Sun, Jin. “Conquering Variability for Robust and Low Power Designs .” 2011. Doctoral Dissertation, University of Arizona. Accessed January 19, 2021. http://hdl.handle.net/10150/145458.

MLA Handbook (7^th Edition):

Sun, Jin. “Conquering Variability for Robust and Low Power Designs .” 2011. Web. 19 Jan 2021.

Vancouver:

Sun J. Conquering Variability for Robust and Low Power Designs . [Internet] [Doctoral dissertation]. University of Arizona; 2011. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10150/145458.

Council of Science Editors:

Sun J. Conquering Variability for Robust and Low Power Designs . [Doctoral Dissertation]. University of Arizona; 2011. Available from: http://hdl.handle.net/10150/145458

University of Alberta

7. Alshehri, Naeem S. Quantification of reservoir uncertainty for optimal decision making.

Degree: PhD, Department of Civil and Environmental Engineering, 2009, University of Alberta

URL: https://era.library.ualberta.ca/files/4x51hj091

► A reliable estimate of the amount of oil or gas in a reservoir is required for development decisions. Uncertainty in reserve estimates affects resource/reserve classification,… (more)

▼ A reliable estimate of the amount of oil or gas in a reservoir is required for development decisions. Uncertainty in reserve estimates affects resource/reserve classification, investment decisions, and development decisions. There is a need to make the best decisions with an appropriate level of technical analysis considering all available data. Current methods of estimating resource uncertainty use spreadsheets or Monte Carlo simulation software with specified probability distributions for each variable. 3-D models may be constructed, but they rarely consider uncertainty in all variables. This research develops an appropriate 2-D model of heterogeneity and uncertainty by integrating 2-D model methodology to account for parameter uncertainty in the mean, which is of primary importance in the input histograms. This research improves reserve evaluation in the presence of geologic uncertainty. Guidelines are developed to: a) select the best modeling scale for making decisions by comparing 2-D vs. 0-D and 3-D models, b) understand parameters that play a key role in reserve estimates, c) investigate how to reduce uncertainties, and d) show the importance of accounting for parameter uncertainty in reserves assessment to get fair global uncertainty by comparing results of Hydrocarbon Initially-in-Place (HIIP) with/without parameter uncertainty. The parameters addressed in this research are those required in the assessment of uncertainty including statistical and geological parameters. This research shows that fixed parameters seriously underestimate the actual uncertainty in resources. A complete setup of methodology for the assessment of uncertainty in the structural surfaces of a reservoir, fluid contacts levels, and petrophysical properties is developed with accounting for parameter uncertainty in order to get fair global uncertainty. Parameter uncertainty can be quantified by several approaches such as the conventional bootstrap (BS), spatial bootstrap (SBS), and conditional-finite-domain (CFD). Real data from a large North Sea reservoir dataset is used to compare those approaches. The CFD approach produced more realistic uncertainty in distributions of the HIIP than those obtained from the BS or SBS approaches. 0-D modeling was used for estimating uncertainty in HIIP with different source of thickness. 2-D is based on geological mapping and can be presented in 2-D maps and checked locally.

Subjects/Keywords: resource; finite; uncertainty; bootstrap; conditional; spatial; model; parameter; HIIP; reserve; hydrocarbon

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APA (6^th Edition):

Alshehri, N. S. (2009). Quantification of reservoir uncertainty for optimal decision making. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/4x51hj091

Chicago Manual of Style (16^th Edition):

Alshehri, Naeem S. “Quantification of reservoir uncertainty for optimal decision making.” 2009. Doctoral Dissertation, University of Alberta. Accessed January 19, 2021. https://era.library.ualberta.ca/files/4x51hj091.

MLA Handbook (7^th Edition):

Alshehri, Naeem S. “Quantification of reservoir uncertainty for optimal decision making.” 2009. Web. 19 Jan 2021.

Vancouver:

Alshehri NS. Quantification of reservoir uncertainty for optimal decision making. [Internet] [Doctoral dissertation]. University of Alberta; 2009. [cited 2021 Jan 19]. Available from: https://era.library.ualberta.ca/files/4x51hj091.

Council of Science Editors:

Alshehri NS. Quantification of reservoir uncertainty for optimal decision making. [Doctoral Dissertation]. University of Alberta; 2009. Available from: https://era.library.ualberta.ca/files/4x51hj091

University of California – San Francisco

8. Biddle-Snead, Charles. Statistical Characterization of Biochemical Network Models.

Degree: Biophysics, 2013, University of California – San Francisco

URL: http://www.escholarship.org/uc/item/1v47h0w2

► Complex systems of numerous interacting biomolecules dictate cellular behavior. To better understand how these systems operate in aggregate, computational models of these systems may be… (more)

▼ Complex systems of numerous interacting biomolecules dictate cellular behavior. To better understand how these systems operate in aggregate, computational models of these systems may be constructed, aligned with experimental data and analyzed to reveal high-order system functionality and produce hypotheses for further experimentation. Different model frameworks offer trade-offs in terms of scale and detail; here, to capture quantitative details of single-cell gene expression data, and to gain insight into the systems generating that data, we use dynamic biochemical reaction networks (BRN) represented by systems ordinary differential equations (ODE). At this scale, challenges arise from both the ODE model framework and the detailed properties of the modeled systems. On the model side, difficulty stems from lack of knowledge of model parameters, their relative certainty when estimated, and from disentangling the often complex relationship between model structure and function. On the system side, behavior is impacted from the small scale details of biomolecular physics as well as the larger scale cellular context in which a system of interest operates.Here, we develop a computational framework to infer data and function constrained parameter posterior distributions and show that these distributions can be used to address challenges in both model analysis and complex system behavior. We apply these methods to models of three biochemical systems: chiefly, we studied the regulatory network controlling flexible GAL1 gene expression in yeast. Our computational approach, together with detailed experimentation, reveals the systems level basis for heterogenous, context-specifc decision making in this circuit.The proposed framework has implications for understanding and quantifying context dependence in natural biochemical networks as it arrises in cell type differentiation, tumorogenesis and elsewhere, and rational control of natural systems through multi-component therapies. Additionally, our approach is a potentially powerful one in the rational design and control of synthetic systems.

Subjects/Keywords: Biology; Cell Signaling; Gene Regulation; Network Modeling; Parameter Uncertainty; Systems Biology

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APA (6^th Edition):

Biddle-Snead, C. (2013). Statistical Characterization of Biochemical Network Models. (Thesis). University of California – San Francisco. Retrieved from http://www.escholarship.org/uc/item/1v47h0w2

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Biddle-Snead, Charles. “Statistical Characterization of Biochemical Network Models.” 2013. Thesis, University of California – San Francisco. Accessed January 19, 2021. http://www.escholarship.org/uc/item/1v47h0w2.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Biddle-Snead, Charles. “Statistical Characterization of Biochemical Network Models.” 2013. Web. 19 Jan 2021.

Vancouver:

Biddle-Snead C. Statistical Characterization of Biochemical Network Models. [Internet] [Thesis]. University of California – San Francisco; 2013. [cited 2021 Jan 19]. Available from: http://www.escholarship.org/uc/item/1v47h0w2.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Biddle-Snead C. Statistical Characterization of Biochemical Network Models. [Thesis]. University of California – San Francisco; 2013. Available from: http://www.escholarship.org/uc/item/1v47h0w2

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Toronto

9. Haque, Yousuf. Essays in Asset Pricing.

Degree: PhD, 2015, University of Toronto

URL: http://hdl.handle.net/1807/70848

► In this thesis I study the relationship between investor behavior and asset pricing from two aspects: First, I examine how investors' learning about a firm's… (more)

▼ In this thesis I study the relationship between investor behavior and asset pricing from two aspects: First, I examine how investors' learning about a firm's stock price in the presence of noisy information impacts the firm's stock return volatility. Second, my co-authors and I investigate how institutional investors vary in the type and extent of skill they exhibit based on prudency requirements and active management. In the first chapter, I examine the relationship between investor learning and firm volatility. Price return volatility is excessive relative to fundamentals (Shiller 1981) and exhibits persistence (Engle 1982). However, empirical research has not focused on providing an explanation that simultaneously addresses both stylized facts. I use a simple rational learning model to predict that the level of return volatility is positively related to the level and uncertainty of cash flow growth rates, and that the dynamics of return volatility reflect the dynamics of investors' uncertainty about cash flow growth rates. Proxying for growth rate variables using analyst earnings forecasts, I show that the data support model predictions. In the second chapter, my co-authors, Mikhail Simutin and Kent Womack, and I examine the relationship between prudency requirements, active management, and the assessment of institutional skill. We hypothesize that the type of skill an institution exhibits depends on how constrained it is by prudency requirements, while the extent of its skill is related to how actively it is managed. We conjecture that less constrained institutions such as hedge funds exhibit skill by trading on near-term information, whereas more constrained institutions such as bank trusts exhibit skill by generating abnormal returns in bad states of the economy. The results from our analysis offer evidence supporting these hypotheses. We employ active share and holdings churn as competing measures of active management and, after controlling for prudency, we find that high active share level is more indicative of skill based trading, whereas high churn level is more consistent with momentum based trading. Advisors/Committee Members: Han, Bing, Kan, Raymond M., Management.

Subjects/Keywords: Institutions; Investing skill; Learning; Parameter uncertainty; Prudency; Volatility; 0508

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APA (6^th Edition):

Haque, Y. (2015). Essays in Asset Pricing. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/70848

Chicago Manual of Style (16^th Edition):

Haque, Yousuf. “Essays in Asset Pricing.” 2015. Doctoral Dissertation, University of Toronto. Accessed January 19, 2021. http://hdl.handle.net/1807/70848.

MLA Handbook (7^th Edition):

Haque, Yousuf. “Essays in Asset Pricing.” 2015. Web. 19 Jan 2021.

Vancouver:

Haque Y. Essays in Asset Pricing. [Internet] [Doctoral dissertation]. University of Toronto; 2015. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1807/70848.

Council of Science Editors:

Haque Y. Essays in Asset Pricing. [Doctoral Dissertation]. University of Toronto; 2015. Available from: http://hdl.handle.net/1807/70848

Virginia Tech

10. Macatula, Romcholo Yulo. Linear Parameter Uncertainty Quantification using Surrogate Gaussian Processes.

Degree: MS, Mathematics, 2020, Virginia Tech

URL: http://hdl.handle.net/10919/99411

► Parameter uncertainty quantification seeks to determine both estimates and uncertainty regarding estimates of model parameters. Example of model parameters can include physical properties such as… (more)

Subjects/Keywords: uncertainty quantification; surrogate models; linear parameter estimation; tomography; bayesian; gaussian process

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Macatula, R. Y. (2020). Linear Parameter Uncertainty Quantification using Surrogate Gaussian Processes. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99411

Chicago Manual of Style (16^th Edition):

Macatula, Romcholo Yulo. “Linear Parameter Uncertainty Quantification using Surrogate Gaussian Processes.” 2020. Masters Thesis, Virginia Tech. Accessed January 19, 2021. http://hdl.handle.net/10919/99411.

MLA Handbook (7^th Edition):

Macatula, Romcholo Yulo. “Linear Parameter Uncertainty Quantification using Surrogate Gaussian Processes.” 2020. Web. 19 Jan 2021.

Vancouver:

Macatula RY. Linear Parameter Uncertainty Quantification using Surrogate Gaussian Processes. [Internet] [Masters thesis]. Virginia Tech; 2020. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10919/99411.

Council of Science Editors:

Macatula RY. Linear Parameter Uncertainty Quantification using Surrogate Gaussian Processes. [Masters Thesis]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99411

Virginia Tech

11. van Wyk, Hans-Werner. A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems.

Degree: PhD, Mathematics, 2012, Virginia Tech

URL: http://hdl.handle.net/10919/27635

► As simulation plays an increasingly central role in modern science and engineering research, by supplementing experiments, aiding in the prototyping of engineering systems or informing… (more)

Subjects/Keywords: uncertainty quantification; parameter identification; elliptic systems; stochastic collocation methods

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APA (6^th Edition):

van Wyk, H. (2012). A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/27635

Chicago Manual of Style (16^th Edition):

van Wyk, Hans-Werner. “A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems.” 2012. Doctoral Dissertation, Virginia Tech. Accessed January 19, 2021. http://hdl.handle.net/10919/27635.

MLA Handbook (7^th Edition):

van Wyk, Hans-Werner. “A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems.” 2012. Web. 19 Jan 2021.

Vancouver:

van Wyk H. A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10919/27635.

Council of Science Editors:

van Wyk H. A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/27635

University of Texas – Austin

12. -1709-7032. Resource allocation in service and logistics systems.

Degree: PhD, Operations Research & Industrial Engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/47042

► Resource allocation is a problem commonly encountered in strategic planning, where a typical objective is to minimize the associated cost or maximize the resulting profit.… (more)

▼ Resource allocation is a problem commonly encountered in strategic planning, where a typical objective is to minimize the associated cost or maximize the resulting profit. It is studied analytically and numerically for service and logistics systems in this dissertation, with the major resource being people, services or trucks. First, a staffing level problem is analyzed for large-scale single-station queueing systems. The system manager operates an Erlang-C queueing system with a quality-of-service (QoS) constraint on the probability that a customer is queued. However, in this model, the arrival rate is uncertain in the sense that even the arrival-rate distribution is not completely known to the manager. Rather, the manager has an estimate of the support of the arrival-rate distribution and the mean. The goal is to determine the number of servers needed to satisfy the quality of service constraint. Two models are explored. First, the constraint is enforced on an overall delay probability, given the probability that different feasible arrival-rate distributions are selected. In the second case, the constraint has to be satisfied by every possible distribution. For both problems, asymptotically optimal solutions are developed based on Halfin-Whitt type scalings. The work is followed by a discussion on solution uniqueness with a joint QoS constraint and a given arrival-rate distribution in multi-station systems. Second, an extension to Naor’s analysis on the joining or balking problem in observable M=M=1 queues and its variant in unobservable M=M=1 queues is presented to incorporate parameter uncertainty. The arrival-rate distribution is known to all, but the exact arrival rate is unknown in both cases. The optimal joining strategies are obtained and compared from the perspectives of individual customers, the social optimizer and the profit maximizer, where differences are recognized between the results for systems with deterministic and stochastic arrival rates. Finally, an integrated ordering and inbound shipping problem is formulated for an assembly plant with a large number of suppliers. The objective is to minimize the annual total cost with a static strategy. Potential transportation modes include full truckload shipping and less than truckload shipping, the former of which allows customized routing while the latter does not. A location-based model is applied in search of near-optimal solutions instead of an exact model with vehicle routing, and numerical experiments are conducted to investigate the insights of the problem. Advisors/Committee Members: Hasenbein, John J. (advisor), Kutanoglu, Erhan (advisor), Bickel, James E. (committee member), Khajavirad, Aida (committee member), Morrice, Douglas J. (committee member).

Subjects/Keywords: Staffing service systems; Parameter uncertainty; Game-theoretic queueing; Inbound shipping

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APA (6^th Edition):

-1709-7032. (2016). Resource allocation in service and logistics systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47042

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-1709-7032. “Resource allocation in service and logistics systems.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 19, 2021. http://hdl.handle.net/2152/47042.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-1709-7032. “Resource allocation in service and logistics systems.” 2016. Web. 19 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-1709-7032. Resource allocation in service and logistics systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/2152/47042.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-1709-7032. Resource allocation in service and logistics systems. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/47042

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

University of California – Santa Cruz

13. Walton, Claire Lydia. The Design and Implementation of Motion Planning Problems Given Parameter Uncertainty.

Degree: Applied Mathematics and Statistics, 2015, University of California – Santa Cruz

URL: http://www.escholarship.org/uc/item/5qx38635

► This thesis explores the potential for utilizing direct methods in optimal control to solve trajectory optimization problems with uncertain parameters. Parameter uncertainty extends traditional optimal… (more)

Subjects/Keywords: Applied mathematics; motion planning; nonlinear control; optimal control; parameter uncertainty; trajectory optimization

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APA (6^th Edition):

Walton, C. L. (2015). The Design and Implementation of Motion Planning Problems Given Parameter Uncertainty. (Thesis). University of California – Santa Cruz. Retrieved from http://www.escholarship.org/uc/item/5qx38635

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Walton, Claire Lydia. “The Design and Implementation of Motion Planning Problems Given Parameter Uncertainty.” 2015. Thesis, University of California – Santa Cruz. Accessed January 19, 2021. http://www.escholarship.org/uc/item/5qx38635.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Walton, Claire Lydia. “The Design and Implementation of Motion Planning Problems Given Parameter Uncertainty.” 2015. Web. 19 Jan 2021.

Vancouver:

Walton CL. The Design and Implementation of Motion Planning Problems Given Parameter Uncertainty. [Internet] [Thesis]. University of California – Santa Cruz; 2015. [cited 2021 Jan 19]. Available from: http://www.escholarship.org/uc/item/5qx38635.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Walton CL. The Design and Implementation of Motion Planning Problems Given Parameter Uncertainty. [Thesis]. University of California – Santa Cruz; 2015. Available from: http://www.escholarship.org/uc/item/5qx38635

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Alberta

14. Deutsch, Jared L. Multivariate Spatial Modeling of Metallurgical Rock Properties.

Degree: PhD, Department of Civil and Environmental Engineering, 2015, University of Alberta

URL: https://era.library.ualberta.ca/files/c1r66j118w

► High resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively measured grade and geomechanical properties constitute an important part of… (more)

▼ High resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively measured grade and geomechanical properties constitute an important part of geometallurgy. The spatial modeling of metallurgical rock properties has unique challenges. Metallurgical properties of interest may average nonlinearly, and the nonlinear behaviour may be unquantified due to substantial costs associated with sample collection and testing. The large scale of the samples presents an additional challenge in the modeling of these variables as the support volume for metallurgical properties may be 1-2 orders of magnitude larger than typical metal assays. Practical challenges including the highly multivariate nature of geometallurgical data sets, undersampling and complex optimization requirements complicate the problem. Addressing these challenges requires an integrated statistical approach. In this thesis, a consistent framework for quantifying and modeling the nonlinear behaviour of metallurgical rock properties is introduced. This integrated approach is composed of three parts: a nonlinear modeling and inference strategy, a multivariate downscaling algorithm, and an integrated geostatistical approach to multivariate modeling of metallurgical properties. The first contribution of this thesis is a novel semi-parametric Bayesian updating algorithm which has been developed to infer nonlinear behaviour given multiscale measurements of metallurgical rock properties and related linear properties. This approach may be applied to fit a power law which is demonstrated to be a flexible model for nonlinear modeling. The second contribution addresses the challenge of highly multiscale data by the development of a direct sequential simulation method for the downscaling of metallurgical rock properties given highly multivariate information. The stochastic downscaling procedure developed is exact and respects intrinsic constraints, such as requirements for non-negativity. The third contribution is the development of a consistent framework for geostatistical modeling of metallurgical variables in the presence of constraints, nonlinear variables, multiscale data, missing data, and complex relationships. This approach, and a number of the algorithms developed in this thesis are applied in a geometallurgical case study of a South American copper-molybdenum porphyry deposit. The thesis statement: an integrated statistical approach for the multivariate spatial modeling of metallurgical rock properties will lead to better mine and mill operation strategies to maximize mine value. Developments in this thesis facilitate the integrated approach which is applied to the case study demonstrating the value of this integrated statistical framework.

Subjects/Keywords: Multivariate simulation; Geometallurgy; Geostatistics; Parameter uncertainty; Nonlinear variables; Multiscale modeling; Multiple imputation; Unequal sampling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Deutsch, J. L. (2015). Multivariate Spatial Modeling of Metallurgical Rock Properties. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/c1r66j118w

Chicago Manual of Style (16^th Edition):

Deutsch, Jared L. “Multivariate Spatial Modeling of Metallurgical Rock Properties.” 2015. Doctoral Dissertation, University of Alberta. Accessed January 19, 2021. https://era.library.ualberta.ca/files/c1r66j118w.

MLA Handbook (7^th Edition):

Deutsch, Jared L. “Multivariate Spatial Modeling of Metallurgical Rock Properties.” 2015. Web. 19 Jan 2021.

Vancouver:

Deutsch JL. Multivariate Spatial Modeling of Metallurgical Rock Properties. [Internet] [Doctoral dissertation]. University of Alberta; 2015. [cited 2021 Jan 19]. Available from: https://era.library.ualberta.ca/files/c1r66j118w.

Council of Science Editors:

Deutsch JL. Multivariate Spatial Modeling of Metallurgical Rock Properties. [Doctoral Dissertation]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/c1r66j118w

Texas A&M University

15. Zhang, Kaiyi. A Simple Innovative Method of Interpreting the Breakthrough Curves in Instantaneous Source Column Tests.

Degree: MS, Water Management and Hydrological Science, 2019, Texas A&M University

URL: http://hdl.handle.net/1969.1/187572

► Instantaneous injection tracer tests can be used effectively to determine solute transport parameters in porous media such as pore velocities and dispersivities, which are usually… (more)

Subjects/Keywords: Advection-dispersion equation; primary parameter estimation; breakthrough curve interpretation; laboratory column test; uncertainty analysis.

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APA (6^th Edition):

Zhang, K. (2019). A Simple Innovative Method of Interpreting the Breakthrough Curves in Instantaneous Source Column Tests. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/187572

Chicago Manual of Style (16^th Edition):

Zhang, Kaiyi. “A Simple Innovative Method of Interpreting the Breakthrough Curves in Instantaneous Source Column Tests.” 2019. Masters Thesis, Texas A&M University. Accessed January 19, 2021. http://hdl.handle.net/1969.1/187572.

MLA Handbook (7^th Edition):

Zhang, Kaiyi. “A Simple Innovative Method of Interpreting the Breakthrough Curves in Instantaneous Source Column Tests.” 2019. Web. 19 Jan 2021.

Vancouver:

Zhang K. A Simple Innovative Method of Interpreting the Breakthrough Curves in Instantaneous Source Column Tests. [Internet] [Masters thesis]. Texas A&M University; 2019. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1969.1/187572.

Council of Science Editors:

Zhang K. A Simple Innovative Method of Interpreting the Breakthrough Curves in Instantaneous Source Column Tests. [Masters Thesis]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/187572

University of Waterloo

16. Kang, Mary. Parameter Estimation and Uncertainty Analysis of Contaminant First Arrival Times at Household Drinking Water Wells.

Degree: 2007, University of Waterloo

URL: http://hdl.handle.net/10012/2715

► Exposure assessment, which is an investigation of the extent of human exposure to a specific contaminant, must include estimates of the duration and frequency of… (more)

▼ Exposure assessment, which is an investigation of the extent of human exposure to a specific contaminant, must include estimates of the duration and frequency of exposure. For a groundwater system, the duration of exposure is controlled largely by the arrival time of the contaminant of concern at a drinking water well. This arrival time, which is normally estimated by using groundwater flow and transport models, can have a range of possible values due to the uncertainties that are typically present in real problems. Earlier arrival times generally represent low likelihood events, but play a crucial role in the decision-making process that must be conservative and precautionary, especially when evaluating the potential for adverse health impacts. Therefore, an emphasis must be placed on the accuracy of the leading tail region in the likelihood distribution of possible arrival times. To demonstrate an approach to quantify the uncertainty of arrival times, a real contaminant transport problem which involves TCE contamination due to releases from the Lockformer Company Facility in Lisle, Illinois is used. The approach used in this research consists of two major components: inverse modelling or parameter estimation, and uncertainty analysis. The parameter estimation process for this case study was selected based on insufficiencies in the model and observational data due to errors, biases, and limitations. A consideration of its purpose, which is to aid in characterising uncertainty, was also made in the process by including many possible variations in attempts to minimize assumptions. A preliminary investigation was conducted using a well-accepted parameter estimation method, PEST, and the corresponding findings were used to define characteristics of the parameter estimation process applied to this case study. Numerous objective functions, which include the well-known L2-estimator, robust estimators (L1-estimators and M-estimators), penalty functions, and deadzones, were incorporated in the parameter estimation process to treat specific insufficiencies. The concept of equifinality was adopted and multiple maximum likelihood parameter sets were accepted if pre-defined physical criteria were met. For each objective function, three procedures were implemented as a part of the parameter estimation approach for the given case study: a multistart procedure, a stochastic search using the Dynamically-Dimensioned Search (DDS), and a test for acceptance based on predefined physical criteria. The best performance in terms of the ability of parameter sets to satisfy the physical criteria was achieved using a Cauchy’s M-estimator that was modified for this study and designated as the LRS1 M-estimator. Due to uncertainties, multiple parameter sets obtained with the LRS1 M-estimator, the L1-estimator, and the L2-estimator are recommended for use in uncertainty analysis. Penalty functions had to be incorporated into the objective function definitions to generate a sufficient number of acceptable parameter sets; in…

Subjects/Keywords: groundwater; contaminant transport; uncertainty; parameter estimation

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APA (6^th Edition):

Kang, M. (2007). Parameter Estimation and Uncertainty Analysis of Contaminant First Arrival Times at Household Drinking Water Wells. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/2715

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kang, Mary. “Parameter Estimation and Uncertainty Analysis of Contaminant First Arrival Times at Household Drinking Water Wells.” 2007. Thesis, University of Waterloo. Accessed January 19, 2021. http://hdl.handle.net/10012/2715.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kang, Mary. “Parameter Estimation and Uncertainty Analysis of Contaminant First Arrival Times at Household Drinking Water Wells.” 2007. Web. 19 Jan 2021.

Vancouver:

Kang M. Parameter Estimation and Uncertainty Analysis of Contaminant First Arrival Times at Household Drinking Water Wells. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10012/2715.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kang M. Parameter Estimation and Uncertainty Analysis of Contaminant First Arrival Times at Household Drinking Water Wells. [Thesis]. University of Waterloo; 2007. Available from: http://hdl.handle.net/10012/2715

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Toronto

17. Gimelfarb, Michael. Thompson Sampling for the Control of a Queue with Demand Uncertainty.

Degree: 2017, University of Toronto

URL: http://hdl.handle.net/1807/79287

►

We study an admission control problem in which the customer arrival rate is unknown and needs to be learned from data using Bayesian inference. Two… (more)

Subjects/Keywords: admission control; Bayesian inference; parameter uncertainty; queueing; Regret bounds; Thompson sampling; 0796

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APA (6^th Edition):

Gimelfarb, M. (2017). Thompson Sampling for the Control of a Queue with Demand Uncertainty. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/79287

Chicago Manual of Style (16^th Edition):

Gimelfarb, Michael. “Thompson Sampling for the Control of a Queue with Demand Uncertainty.” 2017. Masters Thesis, University of Toronto. Accessed January 19, 2021. http://hdl.handle.net/1807/79287.

MLA Handbook (7^th Edition):

Gimelfarb, Michael. “Thompson Sampling for the Control of a Queue with Demand Uncertainty.” 2017. Web. 19 Jan 2021.

Vancouver:

Gimelfarb M. Thompson Sampling for the Control of a Queue with Demand Uncertainty. [Internet] [Masters thesis]. University of Toronto; 2017. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1807/79287.

Council of Science Editors:

Gimelfarb M. Thompson Sampling for the Control of a Queue with Demand Uncertainty. [Masters Thesis]. University of Toronto; 2017. Available from: http://hdl.handle.net/1807/79287

18. Strömberg, Jonas. Parameter uncertainties in groundwater modelling - A study on the effect of calibration method on parameter uncertainties in an inverse stochastic groundwater model .

Degree: Chalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE), 2020, Chalmers University of Technology

URL: http://hdl.handle.net/20.500.12380/301854

► Numerical models can be used to forecast the effects of underground constructions on groundwater conditions. Such forecasts always includes uncertainties, with values of used parameters… (more)

Subjects/Keywords: Stochastic groundwater modelling; GMS MODFLOW; inverse calibration; parameter uncertainty; PEST; Null Space Monte Carlo

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APA (6^th Edition):

Strömberg, J. (2020). Parameter uncertainties in groundwater modelling - A study on the effect of calibration method on parameter uncertainties in an inverse stochastic groundwater model . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/301854

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Strömberg, Jonas. “Parameter uncertainties in groundwater modelling - A study on the effect of calibration method on parameter uncertainties in an inverse stochastic groundwater model .” 2020. Thesis, Chalmers University of Technology. Accessed January 19, 2021. http://hdl.handle.net/20.500.12380/301854.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Strömberg, Jonas. “Parameter uncertainties in groundwater modelling - A study on the effect of calibration method on parameter uncertainties in an inverse stochastic groundwater model .” 2020. Web. 19 Jan 2021.

Vancouver:

Strömberg J. Parameter uncertainties in groundwater modelling - A study on the effect of calibration method on parameter uncertainties in an inverse stochastic groundwater model . [Internet] [Thesis]. Chalmers University of Technology; 2020. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/20.500.12380/301854.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Strömberg J. Parameter uncertainties in groundwater modelling - A study on the effect of calibration method on parameter uncertainties in an inverse stochastic groundwater model . [Thesis]. Chalmers University of Technology; 2020. Available from: http://hdl.handle.net/20.500.12380/301854

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

East Tennessee State University

19. Pei, Ruhang. Revised Model for Antibiotic Resistance in a Hospital.

Degree: MS, Mathematical Sciences, 2015, East Tennessee State University

URL: https://dc.etsu.edu/etd/2471

► In this thesis we modify an existing model for the spread of resistant bacteria in a hospital. The existing model does not account for… (more)

Subjects/Keywords: Antibiotic resistance; Identifiability; Sensitivity Analysis; Parameter Estimation; Uncertainty Analysis; Equilibrium; Stability Analysis; Analysis; Other Mathematics

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APA (6^th Edition):

Pei, R. (2015). Revised Model for Antibiotic Resistance in a Hospital. (Thesis). East Tennessee State University. Retrieved from https://dc.etsu.edu/etd/2471

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Pei, Ruhang. “Revised Model for Antibiotic Resistance in a Hospital.” 2015. Thesis, East Tennessee State University. Accessed January 19, 2021. https://dc.etsu.edu/etd/2471.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Pei, Ruhang. “Revised Model for Antibiotic Resistance in a Hospital.” 2015. Web. 19 Jan 2021.

Vancouver:

Pei R. Revised Model for Antibiotic Resistance in a Hospital. [Internet] [Thesis]. East Tennessee State University; 2015. [cited 2021 Jan 19]. Available from: https://dc.etsu.edu/etd/2471.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pei R. Revised Model for Antibiotic Resistance in a Hospital. [Thesis]. East Tennessee State University; 2015. Available from: https://dc.etsu.edu/etd/2471

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of New Mexico

20. Jia, Lijuan. Toward improved evaluation of large scale hydrologic models: estimation and quantification of parameter uncertainty.

Degree: Civil Engineering, 2015, University of New Mexico

URL: http://hdl.handle.net/1928/25785

► With the development of increasingly complex hydrologic models that use a wide range of parameters to represent hydrologic processes both in space and time, many… (more)

Subjects/Keywords: Uncertainty; Quantification; Sensitivity; Parameter identifiability; Large scale hydrologic model; Climatic gradient; VIC; GLUE; Bayesian; Pareto

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APA (6^th Edition):

Jia, L. (2015). Toward improved evaluation of large scale hydrologic models: estimation and quantification of parameter uncertainty. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/25785

Chicago Manual of Style (16^th Edition):

Jia, Lijuan. “Toward improved evaluation of large scale hydrologic models: estimation and quantification of parameter uncertainty.” 2015. Doctoral Dissertation, University of New Mexico. Accessed January 19, 2021. http://hdl.handle.net/1928/25785.

MLA Handbook (7^th Edition):

Jia, Lijuan. “Toward improved evaluation of large scale hydrologic models: estimation and quantification of parameter uncertainty.” 2015. Web. 19 Jan 2021.

Vancouver:

Jia L. Toward improved evaluation of large scale hydrologic models: estimation and quantification of parameter uncertainty. [Internet] [Doctoral dissertation]. University of New Mexico; 2015. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1928/25785.

Council of Science Editors:

Jia L. Toward improved evaluation of large scale hydrologic models: estimation and quantification of parameter uncertainty. [Doctoral Dissertation]. University of New Mexico; 2015. Available from: http://hdl.handle.net/1928/25785

21. Liu, Hongli. Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications.

Degree: 2019, University of Waterloo

URL: http://hdl.handle.net/10012/14498

► In hydrologic modeling and forecasting applications, many steps are needed. The steps that are relevant to this thesis include watershed discretization, model calibration, and data… (more)

▼ In hydrologic modeling and forecasting applications, many steps are needed. The steps that are relevant to this thesis include watershed discretization, model calibration, and data assimilation. Watershed discretization separates a watershed into homogeneous computational units for depiction in a distributed hydrologic model. Objective identification of an appropriate discretization scheme remains challenging in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. To solve this problem, this thesis contributes to develop an a priori discretization error metrics that can quantify the information loss induced by watershed discretization without running a hydrologic model. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantages of reducing extreme errors and meeting user-specified discretization error targets. In hydrologic model calibration, several uncertainty-based calibration frameworks have been developed to explicitly consider different hydrologic modeling errors, such as parameter errors, forcing and response data errors, and model structure errors. This thesis focuses on climate and flow data errors. The common way of handling climate and flow data uncertainty in the existing calibration studies is perturbing observations with assumed statistical error models (e.g., addictive or multiplicative Gaussian error model) and incorporating them into parameter estimation by integration or repetition with multiple climate and (or) flow realizations. Given the existence of advanced climate and flow data uncertainty estimation methods, this thesis proposes replacing assumed statistical error models with physically-based (and more realistic and convenient) climate and flow ensembles. Accordingly, this thesis contributes developing a climate-flow ensemble based hydrologic model calibration framework. The framework is developed through two stages. The first stage only considers climate data uncertainty, leading to the climate ensemble based hydrologic calibration framework. The framework is parsimonious and can utilize any sources of historical climate ensembles. This thesis demonstrates the method of using the Gridded Ensemble Precipitation and Temperature Estimates dataset (Newman et al., 2015), referred to as N15 here, to derive precipitation and temperature ensembles. Assessment of this framework is conducted using 30 synthetic experiments and 20 real case studies. Results show that the framework generates more robust parameter estimates, reduces the inaccuracy of flow predictions caused by poor quality climate data, and improves the reliability of flow predictions. The second stage adds flow ensemble to the previously developed framework to explicitly consider flow data uncertainty and thus completes the climate-flow ensemble based calibration framework. The complete framework can work with likelihood-free calibration methods. This thesis demonstrates the method of using the…

Subjects/Keywords: Hydrologic modeling; Model calibration; Data assimilation; Streamflow ensemble forecasting; Spatial discretization; Ensemble climate; Ensemble flow; Ensemble Kalman filter; Parameter uncertainty; Data uncertainty; Prediction uncertainty

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APA (6^th Edition):

Liu, H. (2019). Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14498

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liu, Hongli. “Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications.” 2019. Thesis, University of Waterloo. Accessed January 19, 2021. http://hdl.handle.net/10012/14498.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liu, Hongli. “Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications.” 2019. Web. 19 Jan 2021.

Vancouver:

Liu H. Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10012/14498.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu H. Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14498

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Universidade do Minho

22. Mishra, Mayank. A Bayesian approach to NDT Data Fusion for St. Torcato Church .

Degree: 2013, Universidade do Minho

URL: http://hdl.handle.net/1822/28106

► The main objective of this thesis is to combine information gathered from different Non Destructive tests (NDT) (direct and indirect) and fuse it by using… (more)

▼ The main objective of this thesis is to combine information gathered from different Non Destructive tests (NDT) (direct and indirect) and fuse it by using Bayesian approach. Many time practitioners working with NDT data want to choose parameters based on results of different NDT tests with different levels of reliability and uncertainty quantification. As suggested by literature the use of a single technique might not suffice to gain information and the combination of different techniques is recommended. Also for the case of masonry structures it might not be possible to perform destructive tests but since the parameter has to be estimated based on information provided by various NDT data sources coupled with literature information. NDT data from San Torcato Church was used in this thesis to test a Methodology to transform the data into a single and uniform format by the help of Bayesian approach. A simple Matlab Toolbox NDT_FUSION was developed and tested with different models available and modified later by using a Trust Factor which takes into account the weightage of different NDT tests. The developed toolbox is very easy to use since it has Graphical user interface (GUI) and does not required practitioner to learn the complex mathematics involved in calculation behind the Bayesian black box. The data fusion was done at different levels and steps so every time an updating takes place we arrive to a more realistic value of parameter. Two geomechanical parameters namely the Elastic modulus (E) and compressive strength ( fc) of granite blocks from St. Torcato Church were studied in this thesis. The normal probability distribution function for the parameter of interest was calculated by using Jeffrey’s Prior and Conjugate Prior, considering different levels of initial knowledge. The Elastic modulus (E) was updated by using data from Literature knowledge, sonic, ultrasonic and direct compressive strength tests to arrive to a more certain value in form of a posterior distribution. In both the cases the raw data from direct and indirect sources was processed and combined with data fusion toolbox to transform values into statistical distribution. The reliability confidence intervals of parameters were updated every time a new data becomes available providing more broad information. Different levels of uncertainty are present in data fusion system proposed in this report starting from the literature knowledge to direct compression test core data which were quantified and addressed in this thesis. The tests of different reliability levels were weighed by circulating a survey form among professors and graduate students experts in the field to take their opinion. The results of the surveys come was the calculation of Trust Factor to update the spread of the parameters and incorporate in the model to obtain better predication of the parameters. The application developed comes with a Matlab compiler runtime (MCR) installer which allows the application to run on computers without the prerequisite of… Advisors/Committee Members: Ramos, Luís F (advisor), Miranda, Tiago F. S (advisor).

Subjects/Keywords: NDT data fusion; Bayesian updating; Uncertainty; Mechanical parameter; Fusão de dados; Análise bayesiana; Incertezas; Estimativa de parâmetros mecânicos

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Mishra, M. (2013). A Bayesian approach to NDT Data Fusion for St. Torcato Church . (Masters Thesis). Universidade do Minho. Retrieved from http://hdl.handle.net/1822/28106

Chicago Manual of Style (16^th Edition):

Mishra, Mayank. “A Bayesian approach to NDT Data Fusion for St. Torcato Church .” 2013. Masters Thesis, Universidade do Minho. Accessed January 19, 2021. http://hdl.handle.net/1822/28106.

MLA Handbook (7^th Edition):

Mishra, Mayank. “A Bayesian approach to NDT Data Fusion for St. Torcato Church .” 2013. Web. 19 Jan 2021.

Vancouver:

Mishra M. A Bayesian approach to NDT Data Fusion for St. Torcato Church . [Internet] [Masters thesis]. Universidade do Minho; 2013. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1822/28106.

Council of Science Editors:

Mishra M. A Bayesian approach to NDT Data Fusion for St. Torcato Church . [Masters Thesis]. Universidade do Minho; 2013. Available from: http://hdl.handle.net/1822/28106

University of Michigan

23. Steimle, Lauren. Stochastic Dynamic Optimization Under Ambiguity.

Degree: PhD, Industrial & Operations Engineering, 2019, University of Michigan

URL: http://hdl.handle.net/2027.42/149947

► Stochastic dynamic optimization methods are powerful mathematical tools for informing sequential decision-making in environments where the outcomes of decisions are uncertain. For instance, the Markov… (more)

▼ Stochastic dynamic optimization methods are powerful mathematical tools for informing sequential decision-making in environments where the outcomes of decisions are uncertain. For instance, the Markov decision process (MDP) has found success in many application areas, including the evaluation and design of treatment and screening protocols for medical decision making. However, the usefulness of these models is only as good as the data used to parameterize them, and multiple competing data sources are common in many application areas. Unfortunately, the recommendations that result from the optimization process can be sensitive to the data used and thus, susceptible to the impacts of ambiguity in the choices regarding the model's construction. To address the issue of ambiguity in MDPs, we introduce the Multi-model MDP (MMDP) which generalizes a standard MDP by allowing for multiple models of the rewards and transition probabilities. The solution of the MMDP is a policy that considers the performance with respect to the different models and allows for the decision-maker (DM) to explicitly trade-off conflicting sources of data. In this thesis, we study this problem in three parts. In the first part, we study the weighted value problem (WVP) in which the DM’s objective is to find a single policy that maximizes the weighted value of expected rewards in each model. We identify two important variants of this problem: the non-adaptive WVP in which the DM must specify the decision-making strategy before the outcome of ambiguity is observed and the adaptive WVP in which the DM is allowed to adapt to the outcomes of ambiguity. To solve these problems, we develop exact methods and fast approximation methods supported by error bounds. Finally, we illustrate the effectiveness and the scalability of our approach using a case study in preventative blood pressure and cholesterol management that accounts for conflicting published cardiovascular risk models. In the second part, we leverage the special structure of the non-adaptive WVP to design exact decomposition methods for solving MMDPs with a larger number of models. We present a branch-and-cut approach to solve a mixed-integer programming formulation of the problem and a custom branch-and-bound approach. Numerical experiments show that a customized implementation of branch-and-bound significantly outperforms branch-and-cut and allows for the solution of MMDPs with larger numbers of models. In the third part, we extend the MMDP beyond the WVP to consider other objective functions that are sensitive to the ambiguity arising from the existence of multiple models. We modify the branch-and-bound procedure to solve these alternate formulations and compare the resulting policies to policies found using tractable heuristics. Using two case studies, we show that the solution to the mean value problem, wherein all parameters take on their mean values, can perform quite well with respect to several measures of performance under ambiguity. In summary, in this dissertation, we present new… Advisors/Committee Members: Denton, Brian (committee member), Tewari, Ambuj (committee member), Lavieri, Mariel (committee member), Lee, Jon (committee member), Murphy, Susan A (committee member).

Subjects/Keywords: dynamic programming; Markov decision process; stochastic optimization; decomposition; parameter uncertainty; ambiguity; Industrial and Operations Engineering; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Steimle, L. (2019). Stochastic Dynamic Optimization Under Ambiguity. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/149947

Chicago Manual of Style (16^th Edition):

Steimle, Lauren. “Stochastic Dynamic Optimization Under Ambiguity.” 2019. Doctoral Dissertation, University of Michigan. Accessed January 19, 2021. http://hdl.handle.net/2027.42/149947.

MLA Handbook (7^th Edition):

Steimle, Lauren. “Stochastic Dynamic Optimization Under Ambiguity.” 2019. Web. 19 Jan 2021.

Vancouver:

Steimle L. Stochastic Dynamic Optimization Under Ambiguity. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/2027.42/149947.

Council of Science Editors:

Steimle L. Stochastic Dynamic Optimization Under Ambiguity. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/149947

Colorado State University

24. Cody, Brent M. Application of semi-analytical multiphase flow models for the simulation and optimization of geological carbon sequestration.

Degree: PhD, Civil and Environmental Engineering, 2014, Colorado State University

URL: http://hdl.handle.net/10217/82587

► Geological carbon sequestration (GCS) has been identified as having the potential to reduce increasing atmospheric concentrations of carbon dioxide (CO2). However, a global impact will… (more)

▼ Geological carbon sequestration (GCS) has been identified as having the potential to reduce increasing atmospheric concentrations of carbon dioxide (CO2). However, a global impact will only be achieved if GCS is cost effectively and safely implemented on a massive scale. This work presents a computationally efficient methodology for identifying optimal injection strategies at candidate GCS sites having caprock permeability uncertainty. A multi-objective evolutionary algorithm is used to heuristically determine non-dominated solutions between the following two competing objectives: 1) maximize mass of CO2 sequestered and 2) minimize project cost. A semi-analytical algorithm is used to estimate CO2 leakage mass rather than a numerical model, enabling the study of GCS sites having vastly different domain characteristics. The stochastic optimization framework presented herein is applied to a case study of a brine filled aquifer in the Michigan Basin (MB). Twelve optimization test cases are performed to investigate the impact of decision maker (DM) preferences on heuristically determined Pareto-optimal objective function values and decision variable selection. Risk adversity to CO2 leakage is found to have the largest effect on optimization results, followed by degree of caprock permeability uncertainty. This analysis shows that the feasible of GCS at MB test site is highly dependent upon DM risk adversity. Also, large gains in computational efficiency achieved using parallel processing and archiving are discussed. Because the risk assessment and optimization tools used in this effort require large numbers of simulation calls, it important to choose the appropriate level of complexity when selecting the type of simulation model. An additional premise of this work is that an existing multiphase semi-analytical algorithm used to estimate key system attributes (i.e. pressure distribution, CO2 plume extent, and fluid migration) may be further improved in both accuracy and computational efficiency. Herein, three modifications to this algorithm are presented and explored including 1) solving for temporally averaged flow rates at each passive well at each time step, 2) using separate pressure response functions depending on fluid type, and 3) applying a fixed point type iterative global pressure solution to eliminate the need to solve large sets of linear equations. The first two modifications are aimed at improving accuracy while the third focuses upon computational efficiency. Results show that, while one modification may adversely impact the original algorithm, significant gains in leakage estimation accuracy and computational efficiency are obtained by implementing two of these modifications. Finally, in an effort to further enhance the GCS optimization framework, this work presents a performance comparison between a recently proposed multi-objective gravitational search algorithm (MOGSA) and the well-established fast non-dominated sorting genetic algorithm (NSGA-II). Both techniques are used to… Advisors/Committee Members: Bau, Domenico (advisor), Labadie, John (committee member), Sale, Tom (committee member), Chong, Edwin (committee member).

Subjects/Keywords: geological carbon sequestration; gravitational search algorithm; multi-objective optimization; NSGA-II; parameter uncertainty; semi-analytical modeling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cody, B. M. (2014). Application of semi-analytical multiphase flow models for the simulation and optimization of geological carbon sequestration. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/82587

Chicago Manual of Style (16^th Edition):

Cody, Brent M. “Application of semi-analytical multiphase flow models for the simulation and optimization of geological carbon sequestration.” 2014. Doctoral Dissertation, Colorado State University. Accessed January 19, 2021. http://hdl.handle.net/10217/82587.

MLA Handbook (7^th Edition):

Cody, Brent M. “Application of semi-analytical multiphase flow models for the simulation and optimization of geological carbon sequestration.” 2014. Web. 19 Jan 2021.

Vancouver:

Cody BM. Application of semi-analytical multiphase flow models for the simulation and optimization of geological carbon sequestration. [Internet] [Doctoral dissertation]. Colorado State University; 2014. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10217/82587.

Council of Science Editors:

Cody BM. Application of semi-analytical multiphase flow models for the simulation and optimization of geological carbon sequestration. [Doctoral Dissertation]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/82587

University of Miami

25. Chen, Gino. Mesoscale Organized Convection in Climate Models: A Stochastic Scheme and Uncertainty Quantification.

Degree: PhD, Meteorology and Physical Oceanography (Marine), 2018, University of Miami

URL: https://scholarlyrepository.miami.edu/oa_dissertations/2137

► Mesoscale organized convection is generally misrepresented in the large-scale convective parameterizations used in contemporary climate models. This impacts extreme weather events (e.g., Madden-Jullian Oscillation (MJO))… (more)

▼ Mesoscale organized convection is generally misrepresented in the large-scale convective parameterizations used in contemporary climate models. This impacts extreme weather events (e.g., Madden-Jullian Oscillation (MJO)) and the general circulation driven by the significant amount of latent heat released from mesoscale organized convection. Studies show that the missing processes could be partially recovered by embedding a 2D cloud-resolving model in each GCM columns, i.e., super- parameterization. Despite successfully resolving the MJO, the study of mesoscale organization mechanism across the CRM and GCM cells remains sparse in this multiscale modeling framework. We applied rigorous detection and hierarchical clustering algorithms on the 3-hourly 2D resolved Mesoscale Convective Systems (MCSs) embedded in the cloud-permitting Super-Parameterized Community Atmosphere Model 5.2 (SPCAM). We then examined the fields of a long-lived and large MCS cluster at the central Pacific. The MCS cluster shows a squall line-like circulation throughout the lifecycle in SPCAM. The growth of deep shear surrounding the MCS cluster is presumably caused by the upgradient momentum transport of squall line organization. We simultaneously obtained the 3-hourly CAM cumulus parameterization outputs based on the timestep-wise perfect initial conditions given by SPCAM. This allows pure model physics comparison without introducing initial condition errors. The results show that CAM has a systematically biased stratiform cooling and moistening response below 3km to the given SPCAM deep convection favoring conditions. We showed that this bias is mainly due to the CAM’s stratiform microphysics scheme. The mesoscale organization in SPCAM thus provides a baseline for improvements of convective parameterization of CAM. The details of the systematic differences are revealed by a composite analysis. Results show SPCAM has a realistic growth to decay deep convection mode dominant in the large-scale heating and moisture sink in the composite. On the other hand, CAM strongly favors a steady stratiform dipole mode. CAM also shows little to no deep convection variation in the MCS organized environment given by SPCAM. The lack of variation commonly seen in deterministically parameterized large-scale models is often remedied by stochastic parameterization to represent the missing subgrid processes. By decomposing CAM’s cumulus parameterization schemes, we proposed a stochastic scheme to represent the mesoscale organization processes in CAM using the results from SPCAM. We performed a simple model proof-of-concept study to reach the goal of applying the stochastic scheme to a complex climate model. The time-independent perturbed parameter scheme shows comparable forecast skill when compared to the standard stochastic schemes. This time-independent perturbation scheme allows us to treat the forecast model as a black box with minimal intrusion to the model codes. The major standout of the new scheme is its ability to significantly reduce the simulation cost by… Advisors/Committee Members: Ben Kirtman, Mohamed Iskandarani, Sharanya Majumdar, Omar Knio.

Subjects/Keywords: mesoscale convective organization; moist convection; super-parameterization; stochastic parameterization; time-independent perturbed parameter scheme; uncertainty quantification

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chen, G. (2018). Mesoscale Organized Convection in Climate Models: A Stochastic Scheme and Uncertainty Quantification. (Doctoral Dissertation). University of Miami. Retrieved from https://scholarlyrepository.miami.edu/oa_dissertations/2137

Chicago Manual of Style (16^th Edition):

Chen, Gino. “Mesoscale Organized Convection in Climate Models: A Stochastic Scheme and Uncertainty Quantification.” 2018. Doctoral Dissertation, University of Miami. Accessed January 19, 2021. https://scholarlyrepository.miami.edu/oa_dissertations/2137.

MLA Handbook (7^th Edition):

Chen, Gino. “Mesoscale Organized Convection in Climate Models: A Stochastic Scheme and Uncertainty Quantification.” 2018. Web. 19 Jan 2021.

Vancouver:

Chen G. Mesoscale Organized Convection in Climate Models: A Stochastic Scheme and Uncertainty Quantification. [Internet] [Doctoral dissertation]. University of Miami; 2018. [cited 2021 Jan 19]. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/2137.

Council of Science Editors:

Chen G. Mesoscale Organized Convection in Climate Models: A Stochastic Scheme and Uncertainty Quantification. [Doctoral Dissertation]. University of Miami; 2018. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/2137

Iowa State University

26. Mineroff, Joshua. An optimization and uncertainty quantification framework for patient-specific cardiac modeling.

Degree: 2018, Iowa State University

URL: https://lib.dr.iastate.edu/etd/17269

► Patient-specific cardiac models can be used to improve the diagnosis of cardiovascular diseases. However, practical application of these models is impeded by the computational costs… (more)

▼ Patient-specific cardiac models can be used to improve the diagnosis of cardiovascular diseases. However, practical application of these models is impeded by the computational costs and numerical uncertainties of fitting them to clinical measurements from individual patients. Reliable and efficient model tuning within medically-appropriate error bounds is a requirement for practical deployment in the time-constrained environment of the clinic. In this work, we present a framework to efficiently tune parameters of patient-specific mechanistic models using routinely acquired non-invasive patient data with a hybrid particle swarm and pattern search optimization algorithm. The proposed framework is used to tune full-cycle lumped parameter circulatory models using clinical data obtained from patients as well as canine subjects; showing that the framework can be easily adapted to optimize cross-species models. It is also used to simultaneously obtain the unloaded geometry and passive myocardial material parameters of four left-ventricular cardiac finite element models constructed from canine subject MRI data. This demonstrates that the proposed approach can support the use of complex models to obtain data that cannot be directly measured. The patients gave informed consent and the canine subject studies were approved by the local Institutional Review Boards. The optimized results in all case studies were within acceptable error tolerances. Additionally, the framework is extended to include uncertainty quantification – supporting model tuning with often-unreliable data sources that are ill-suited to a deterministic approach. The proposed approach for probabilistic model tuning discovers distributions of model inputs which generate target output distributions. Probabilistic sampling is performed using a model surrogate for computational efficiency and a general distribution parameterization is used to describe each input. The approach is tested on four test cases using CircAdapt, a cardiac circulatory model. Three test cases are synthetic, aiming to match the output distributions generated using known reference input data distributions, while the fourth example uses real-world patient data for the output distributions to obtain the input distribution. The results demonstrate accurate reproduction of the target output distributions, with accurate recreation of reference inputs for the three synthetic examples. Overall, this work automates the use of biomechanics and circulatory cardiac models in both clinical and research environments by ameliorating the tedious process of manually fitting model parameters and supports the use of more complex models in practice through the quantification of error.

Subjects/Keywords: Cardiac biomechanics; Design; Lumped-parameter circulation model; Optimization; Patient-specific modeling; Uncertainty quantification; Art and Design; Engineering; Mechanical Engineering

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APA (6^th Edition):

Mineroff, J. (2018). An optimization and uncertainty quantification framework for patient-specific cardiac modeling. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/17269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mineroff, Joshua. “An optimization and uncertainty quantification framework for patient-specific cardiac modeling.” 2018. Thesis, Iowa State University. Accessed January 19, 2021. https://lib.dr.iastate.edu/etd/17269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mineroff, Joshua. “An optimization and uncertainty quantification framework for patient-specific cardiac modeling.” 2018. Web. 19 Jan 2021.

Vancouver:

Mineroff J. An optimization and uncertainty quantification framework for patient-specific cardiac modeling. [Internet] [Thesis]. Iowa State University; 2018. [cited 2021 Jan 19]. Available from: https://lib.dr.iastate.edu/etd/17269.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mineroff J. An optimization and uncertainty quantification framework for patient-specific cardiac modeling. [Thesis]. Iowa State University; 2018. Available from: https://lib.dr.iastate.edu/etd/17269

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

27. Pascu, V. (author). Reliable Wind Turbine Control Design: A Study of Achievable Control Performance under Design Uncertainty.

Degree: 2015, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:2c18fcf6-5376-4743-a274-fc2b8ea35515

►

Wind power has proven to be one of the most versatile forms of renewable energy. Similarly, offshore wind is currently emerging as the most promising… (more)

Subjects/Keywords: wind energy systems; control systems; linear parameter-varying control; robust control; ice accretion; scour; reliable wind turbine control design; uncertainty

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APA (6^th Edition):

Pascu, V. (. (2015). Reliable Wind Turbine Control Design: A Study of Achievable Control Performance under Design Uncertainty. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2c18fcf6-5376-4743-a274-fc2b8ea35515

Chicago Manual of Style (16^th Edition):

Pascu, V (author). “Reliable Wind Turbine Control Design: A Study of Achievable Control Performance under Design Uncertainty.” 2015. Masters Thesis, Delft University of Technology. Accessed January 19, 2021. http://resolver.tudelft.nl/uuid:2c18fcf6-5376-4743-a274-fc2b8ea35515.

MLA Handbook (7^th Edition):

Pascu, V (author). “Reliable Wind Turbine Control Design: A Study of Achievable Control Performance under Design Uncertainty.” 2015. Web. 19 Jan 2021.

Vancouver:

Pascu V(. Reliable Wind Turbine Control Design: A Study of Achievable Control Performance under Design Uncertainty. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2021 Jan 19]. Available from: http://resolver.tudelft.nl/uuid:2c18fcf6-5376-4743-a274-fc2b8ea35515.

Council of Science Editors:

Pascu V(. Reliable Wind Turbine Control Design: A Study of Achievable Control Performance under Design Uncertainty. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:2c18fcf6-5376-4743-a274-fc2b8ea35515

28. SUN ZEYU. MANAGEMENT FORECAST AND RISK PARAMETER UNCERTAINTY.

Degree: 2016, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/126069

Subjects/Keywords: Voluntary Disclosure; Management Earnings Forecast; Estimation Risk; Parameter Uncertainty

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APA (6^th Edition):

ZEYU, S. (2016). MANAGEMENT FORECAST AND RISK PARAMETER UNCERTAINTY. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/126069

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

ZEYU, SUN. “MANAGEMENT FORECAST AND RISK PARAMETER UNCERTAINTY.” 2016. Thesis, National University of Singapore. Accessed January 19, 2021. http://scholarbank.nus.edu.sg/handle/10635/126069.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

ZEYU, SUN. “MANAGEMENT FORECAST AND RISK PARAMETER UNCERTAINTY.” 2016. Web. 19 Jan 2021.

Vancouver:

ZEYU S. MANAGEMENT FORECAST AND RISK PARAMETER UNCERTAINTY. [Internet] [Thesis]. National University of Singapore; 2016. [cited 2021 Jan 19]. Available from: http://scholarbank.nus.edu.sg/handle/10635/126069.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

ZEYU S. MANAGEMENT FORECAST AND RISK PARAMETER UNCERTAINTY. [Thesis]. National University of Singapore; 2016. Available from: http://scholarbank.nus.edu.sg/handle/10635/126069

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. PULKIT CHHABRA. MODELING AND OPTIMIZATION OF BIODIESEL REACTOR AND FEEDSTOCK.

Degree: 2018, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/152302

Subjects/Keywords: Biodiesel; Kinetics; Oil; Parameter Estimation; Meta-modeling; Uncertainty

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APA (6^th Edition):

CHHABRA, P. (2018). MODELING AND OPTIMIZATION OF BIODIESEL REACTOR AND FEEDSTOCK. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/152302

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

CHHABRA, PULKIT. “MODELING AND OPTIMIZATION OF BIODIESEL REACTOR AND FEEDSTOCK.” 2018. Thesis, National University of Singapore. Accessed January 19, 2021. http://scholarbank.nus.edu.sg/handle/10635/152302.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

CHHABRA, PULKIT. “MODELING AND OPTIMIZATION OF BIODIESEL REACTOR AND FEEDSTOCK.” 2018. Web. 19 Jan 2021.

Vancouver:

CHHABRA P. MODELING AND OPTIMIZATION OF BIODIESEL REACTOR AND FEEDSTOCK. [Internet] [Thesis]. National University of Singapore; 2018. [cited 2021 Jan 19]. Available from: http://scholarbank.nus.edu.sg/handle/10635/152302.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

CHHABRA P. MODELING AND OPTIMIZATION OF BIODIESEL REACTOR AND FEEDSTOCK. [Thesis]. National University of Singapore; 2018. Available from: http://scholarbank.nus.edu.sg/handle/10635/152302

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

30. Myers, Elim Rosalva. COUPLING CONSTRAINT BOUNDARY MAPPING IN THE PROCESS DESIGN PARAMETER SPACE WITH COMMERCIAL PROCESS SIMULATOR TO ESTIMATE PROCESS DESIGN RELIABILITY.

Degree: PhD, Chemical & Petroleum Engineering, 2010, University of Kansas

URL: http://hdl.handle.net/1808/7388

► Chemical process designs include safety factors to compensate for inherent parameter uncertainty in the design process. These safety factors require additional capital and operating expenses.… (more)

▼ Chemical process designs include safety factors to compensate for inherent parameter uncertainty in the design process. These safety factors require additional capital and operating expenses. Since these factors are based on rules of thumb, they may be ineffective and wasteful. The certainty that a process will meet process constraints during normal operation despite the underlying uncertainty in process design parameters is the process design reliability. The estimation of the reliability of a proposed design and an evaluation of the safety factor effectiveness in increasing reliability would identify which equipment is unnecessarily oversized, which is critically undersized and which uncertainties are the principal contributors to low reliability. The designer could then adjust the safety factors to optimize reliability, capital investment and operating expenses. Traditionally, reliability has been evaluated by conventional Monte Carlo integration. This methodology is computationally too expensive since it requires a large number of model simulations. Recalculation for sensitivity analysis is prohibitive. An alternative is required. Furthermore, an evaluation tool that assists designers to maximize reliability while minimizing cost would be substantially useful in a commercial process simulator. A computationally efficient methodology for estimating reliability, Monte Carlo integration of the c-constraints mapped onto the p-parameter space, was developed, improved and coupled with a widely available commercial process simulator, CHEMCAD. In this methodology, the design's success region is mapped onto the parameter space. Sets of parameter values falling on the constraint boundary of the success region are found through process simulation coupled with a search algorithm. This search is independent of the parameter uncertainty. These boundary points are then connected via hyper-planes through interpolation. These connected hyper-planes represent a hyper-volume. Parameter sets falling within this volume successfully meet all constraints. Monte Carlo integration of the parameter uncertainty within this volume leads to an estimate of the process design reliability. This integration does not require process simulations. The procedure adds new boundary points in the regions of greatest uncertainty to improve the reliability estimate. The methodology requires two to three orders of magnitude fewer simulations than conventional Monte Carlo. The method is coupled with CHEMCAD through an EXCEL-driven central program making the method widely available to the process design community. Safety factor impact on reliability can be readily evaluated. Viability and efficiency are demonstrated using distillation case studies based on industrial challenges. Advisors/Committee Members: Howat, Colin S. (advisor), Camarda, Kyle (cmtemember), Green, Don W. (cmtemember), Southard, Marylee (cmtemember), Prescott, Glenn (cmtemember).

Subjects/Keywords: Chemical engineering; Design; Parameter; Process; Reliability; Uncertainty

…statistical description of parameter uncertainty for the first and second case studies… …equations and statistical description of parameter uncertainty for the third and fourth case… …example A/B distillation column… 82 Statistical description of parameter uncertainty… …includes safety factors to compensate for inherent parameter uncertainty in the design process… …parameter uncertainty. A brief overview is presented here. Appendix C contains more literature…

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APA (6^th Edition):

Myers, E. R. (2010). COUPLING CONSTRAINT BOUNDARY MAPPING IN THE PROCESS DESIGN PARAMETER SPACE WITH COMMERCIAL PROCESS SIMULATOR TO ESTIMATE PROCESS DESIGN RELIABILITY. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/7388

Chicago Manual of Style (16^th Edition):

Myers, Elim Rosalva. “COUPLING CONSTRAINT BOUNDARY MAPPING IN THE PROCESS DESIGN PARAMETER SPACE WITH COMMERCIAL PROCESS SIMULATOR TO ESTIMATE PROCESS DESIGN RELIABILITY.” 2010. Doctoral Dissertation, University of Kansas. Accessed January 19, 2021. http://hdl.handle.net/1808/7388.

MLA Handbook (7^th Edition):

Myers, Elim Rosalva. “COUPLING CONSTRAINT BOUNDARY MAPPING IN THE PROCESS DESIGN PARAMETER SPACE WITH COMMERCIAL PROCESS SIMULATOR TO ESTIMATE PROCESS DESIGN RELIABILITY.” 2010. Web. 19 Jan 2021.

Vancouver:

Myers ER. COUPLING CONSTRAINT BOUNDARY MAPPING IN THE PROCESS DESIGN PARAMETER SPACE WITH COMMERCIAL PROCESS SIMULATOR TO ESTIMATE PROCESS DESIGN RELIABILITY. [Internet] [Doctoral dissertation]. University of Kansas; 2010. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1808/7388.

Council of Science Editors:

Myers ER. COUPLING CONSTRAINT BOUNDARY MAPPING IN THE PROCESS DESIGN PARAMETER SPACE WITH COMMERCIAL PROCESS SIMULATOR TO ESTIMATE PROCESS DESIGN RELIABILITY. [Doctoral Dissertation]. University of Kansas; 2010. Available from: http://hdl.handle.net/1808/7388

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