Tesis sobre el tema "Parameter uncertainty"
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Sui, Liqi. "Uncertainty management in parameter identification". Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2330/document.
Texto completoIn order to obtain more predictive and accurate simulations of mechanical behaviour in the practical environment, more and more complex material models have been developed. Nowadays, the characterization of material properties remains a top-priority objective. It requires dedicated identification methods and tests in conditions as close as possible to the real ones. This thesis aims at developing an effective identification methodology to find the material property parameters, taking advantages of all available information. The information used for the identification is theoretical, experimental, and empirical: the theoretical information is linked to the mechanical models whose uncertainty is epistemic; the experimental information consists in the full-field measurement whose uncertainty is aleatory; the empirical information is related to the prior information with epistemic uncertainty as well. The main difficulty is that the available information is not always reliable and its corresponding uncertainty is heterogeneous. This difficulty is overcome by the introduction of the theory of belief functions. By offering a general framework to represent and quantify the heterogeneous uncertainties, the performance of the identification is improved. The strategy based on the belief function is proposed to identify macro and micro elastic properties of multi-structure materials. In this strategy, model and measurement uncertainties arc analysed and quantified. This strategy is subsequently developed to take prior information into consideration and quantify its corresponding uncertainty
Mao, Yi. "Domain knowledge, uncertainty, and parameter constraints". Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37295.
Texto completoClouse, Randy Wayne. "Evaluation of GLEAMS considering parameter uncertainty". Thesis, Virginia Tech, 1996. http://hdl.handle.net/10919/44516.
Texto completoClouse, Randy W. "Evaluation of GLEAMS considering parameter uncertainty /". This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-09042008-063009/.
Texto completoTao, Zuoyu. "Improved uncertainty estimates for geophysical parameter retrieval". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61516.
Texto completoThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 167-169).
Algorithms for retrieval of geophysical parameters from radiances measured by instruments onboard satellites play a large role in helping scientists monitor the state of the planet. Current retrieval algorithms based on neural networks are superior in accuracy and speed compared to physics-based algorithms like iterated minimum variance (IMV). However, they do not have any form of error estimation, unlike IMV. This thesis examines the suitability of several different approaches to adding in confidence intervals and other methods of error estimation to the retrieval algorithm, as well as alternative machine learning methods that can both retrieve the parameters desired and assign error bars. Test datasets included both current generation operational instruments like AIRS/AMSU, as well as a hypothetical future hyper- spectral microwave sounder. Mixture density networks (MDN) and Sparse Pseudo Input Gaussian processes (SPGP) were found to be the most accurate at variance prediction. Both of these are novel methods in the field of remote sensing. MDNs also had similar training and testing time to neural networks, while SPGPs often took three times as long to train in typical cases. As a baseline, neural networks trained to estimate variance were also tested, but found to be lacking in accuracy and reliability compared to the other methods.
by Zuoyu Tao.
M.Eng.
Kumar, Dipmani. "Parameter uncertainty in nonpoint source pollution modeling". Diss., This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-10042006-143856/.
Texto completoGreen, Nathan. "Optimal intervention of epidemic models with parameter uncertainty". Thesis, University of Liverpool, 2005. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:76732.
Texto completoHagen, David Robert. "Parameter and topology uncertainty for optimal experimental design". Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90148.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 157-169).
A major effort of systems biology is the building of accurate and detailed models of biological systems. Because biological models are large, complex, and highly nonlinear, building accurate models requires large quantities of data and algorithms appropriate to translate this data into a model of the underlying system. This thesis describes the development and application of several algorithms for simulation, quantification of uncertainty, and optimal experimental design for reducing uncertainty. We applied a previously described algorithm for choosing optimal experiments for reducing parameter uncertainty as estimated by the Fisher information matrix. We found, using a computational scenario where the true parameters were unknown, that the parameters of the model could be recovered from noisy data in a small number of experiments if the experiments were chosen well. We developed a method for quickly and accurately approximating the probability distribution over a set of topologies given a particular data set. The method was based on a linearization applied at the maximum a posteriori parameters. This method was found to be about as fast as existing heuristics but much closer to the true probability distribution as computed by an expensive Monte Carlo routine. We developed a method for optimal experimental design to reduce topology uncertainty based on the linear method for topology probability. This method was a Monte Carlo method that used the linear method to quickly evaluate the topology uncertainty that would result from possible data sets of each candidate experiment. We applied the method to a model of ErbB signaling. Finally, we developed a method for reducing the size of models defined as rule-based models. Unlike existing methods, this method handles compartments of models and allows for cycles between monomers. The methods developed here generally improve the detail at which models can be built, as well as quantify how well they have been built and suggest experiments to build them even better.
by David Robert Hagen.
Ph. D.
Macatula, Romcholo Yulo. "Linear Parameter Uncertainty Quantification using Surrogate Gaussian Processes". Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99411.
Texto completoMaster of Science
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 density, growth rates, or even deblurred images. Previous work has shown that replacing data with a surrogate model can provide promising estimates with low uncertainty. We extend the previous methods in the specific field of linear models. Theoretical results are tested on simulated computed tomography problems.
Blasone, Roberta-Serena. "Parameter estimation and uncertainty assessment in hydrological modelling". Kgs. Lyngby, 2007. http://www.er.dtu.dk/publications/fulltext/2007/MR2007-105.pdf.
Texto completoGiampellegrini, Laurent. "Uncertainty in correlation-driven operational modal parameter estimation". Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1445512/.
Texto completoVrugt, Jasper Alexander. "Towards improved treatment of parameter uncertainty in hydrologic modeling". [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2004. http://dare.uva.nl/document/77207.
Texto completoBodine, Andrew James. "The Effect of Item Parameter Uncertainty on Test Reliability". The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1343316705.
Texto completoNoronha, Alston Marian Lee Jejung. "Information theory approach to quantifying parameter uncertainty in groundwater modeling". Diss., UMK access, 2005.
Buscar texto completo"A thesis in civil engineering." Typescript. Advisor: Jejung Lee. Vita. Title from "catalog record" of the print edition Description based on contents viewed March 12, 2007. Includes bibliographical references (leaves 96-100). Online version of the print edition.
BEZERRA, BERNARDO VIEIRA. "STOCHASTIC HYDROTHERMAL SCHEDULING WITH PARAMETER UNCERTAINTY IN THE STREAMFLOW MODELS". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=25337@1.
Texto completoCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
O objetivo do planejamento da operação hidrotérmica de médio e longo prazo é definir as metas para geração de cada hidroelétrica e termelétrica, a fim de atender à carga ao menor custo esperado de operação e respeitando as restrições operacionais. Algoritmos de Programação Dinâmica Estocástica (PDE) e de Programação Dinâmica Dual Estocástica (PDDE) têm sido amplamente aplicados para determinar uma política operativa ideal o despacho hidrotérmico. Em ambas as abordagens a estocasticidade das afluências é comumente produzida por modelos periódicos autoregressivos de lag p - PAR(p), cuja estimativa dos parâmetros é baseada nos dados históricos disponíveis. Como os estimadores são funções de fenômenos aleatórios, além da incerteza sobre as vazões, também há incerteza sobre os parâmetros estatísticos, o que não é capturado no modelo PAR (p) padrão. A existência de incerteza nos parâmetros significa que há um risco de que a política da operação hidrotérmica planejada não será a ótima. O objetivo desta tese é apresentar uma metodologia para incorporar a incerteza dos parâmetros do modelo PAR (p) no problema de programação estocástica hidrotérmica. São apresentados estudos de caso ilustrando o impacto da incerteza dos parâmetros nos custos operativos do sistema e como uma política operativa que incorpore esta incerteza pode reduzir este impacto.
The objective of the medium and long-term hydrothermal scheduling problem is to define operational target for each power plant in order to meet the load at the lowest expected cost and respecting the operational constraints. Stochastic Dynamic Programming (SDP) and Stochastic Dual Dynamic Programming (SDDP) algorithms have been widely applied to determine the optimal operating policy for the hydrothermal dispatch. In both approaches, the stochasticity of the inflows is usually produced by periodic auto-regressive models - PAR (p), whose parameters are estimated based on available historical data. As the estimators are a function of random phenomena, besides the inflows uncertainty there is statistical parameter uncertainty, which is not captured in the standard PAR (p) model. The existence of uncertainty in the parameters means that there is a risk that the hydrothermal operating policy will not be optimal. This thesis presents a methodology to incorporate the PAR(p) parameter uncertainty into stochastic hydrothermal scheduling and to assess the resulting impact on the computation of a hydro operations policy. Case studies are presented illustrating the impact of parameter uncertainty in the system operating costs and how an operating policy that incorporates this uncertainty can reduce this impact.
Greenall, Nicholas Robert. "Parameter extraction and uncertainty in terahertz time-domain spectroscopic measurements". Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/19045/.
Texto completoHow, Jonathan P. "Robust control design with real parameter uncertainty using absolute stability". Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12538.
Texto completoGRSN 640480
Includes bibliographical references (p. 185-198).
by Jonathan P. How.
Ph.D.
Plaskett, Joseph H. "Parameter uncertainty and modeling of sludge dewatering in one dimension". PDXScholar, 1992. https://pdxscholar.library.pdx.edu/open_access_etds/4432.
Texto completoMangado, López Nerea. "Cochlear implantation modeling and functional evaluation considering uncertainty and parameter variability". Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/586214.
Texto completoRecientes mejoras en el desarrollo del modelado computacional han facilitado importantes avances en herramientas predictivas para simular procesos quirúrgicos maximizando así los resultados de la cirugía. Esta tesis se focaliza en la cirugía de implantación coclear. Dicha técnica permite recuperar el sentido auditivo a pacientes con sordera severa. Sin embargo, el éxito de la intervención depende de un conjunto de factores, difíciles de controlar o incluso impredecibles. Por este motivo, existe una gran variabilidad interindividual, lo cual lleva a considerar la predicción de esta cirugía como un proceso complejo. El objetivo de esta tesis es el desarrollo de herramientas computacionales para la evaluación funcional de dicha cirugía. Para este fi n, esta tesis aborda una serie de retos, entre ellos la optimización automática de la respuesta neural inducida por el implante coclear y la evaluación numérica de grandes grupos de pacientes.
Binder, Tanja [Verfasser] y Ekaterina [Akademischer Betreuer] Kostina. "Optimization under uncertainty : robust parameter estimation with erroneous measurements and uncertain model coefficients / Tanja Binder. Betreuer: Ekaterina Kostina". Marburg : Philipps-Universität Marburg, 2013. http://d-nb.info/1032315245/34.
Texto completoDurisek, Nicholas Joseph. "Simultaneous overall measurement uncertainty reduction for multi-parameter macro-measurement system design /". The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487942739808246.
Texto completoSöderström, Ulf. "Monetary policy under uncertainty". Doctoral thesis, Handelshögskolan i Stockholm, Samhällsekonomi (S), 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-646.
Texto completoDiss. Stockholm : Handelshögskolan, 1999
Blanchard, Emmanuel. "Polynomial Chaos Approaches to Parameter Estimation and Control Design for Mechanical Systems with Uncertain Parameters". Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/26727.
Texto completoPh. D.
Sar, Preeti. "Eco-Inspired Robust Control Design Algorithm For Linear Systems with Real Parameter Uncertainty". The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1367439491.
Texto completoAlyaseri, Isam. "QUALITATIVE AND QUANTITATIVE PROCEDURE FOR UNCERTAINTY ANALYSIS IN LIFE CYCLE ASSESSMENT OF WASTEWATER SOLIDS TREATMENT PROCESSES". OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/795.
Texto completoXu, Yijun. "Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods". Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/97876.
Texto completoPHD
Chandavarkar, Rohan Vivek. "Eco-inspired Robust Control Design for Linear Time-Invariant systems with Real Parameter Uncertainty". The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1373467190.
Texto completoQin, Wenyi. "Many server queueing models with heterogeneous servers and parameter uncertainty with customer contact centre applications". Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33167.
Texto completoShimp, Samuel Kline III. "Vehicle Sprung Mass Parameter Estimation Using an Adaptive Polynomial-Chaos Method". Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/32056.
Texto completoMaster of Science
Doehr, Rachel M. "Adventures at the Zero Lower Bound: A Bayesian Time-Varying Parameter Vector Autoregressive Analysis of Monetary Policy Uncertainty Shocks". Scholarship @ Claremont, 2016. http://scholarship.claremont.edu/cmc_theses/1318.
Texto completoZhang, Xuesong. "Evaluating and developing parameter optimization and uncertainty analysis methods for a computationally intensive distributed hydrological model". [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3091.
Texto completoBeckers, Joseph. "Modelling the Oro Moraine multi-aquifer system, role of geology, numerical model, parameter estimation and uncertainty". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0020/NQ38218.pdf.
Texto completoDemaria, Eleonora Maria. "EVALUATING THE IMPACTS OF INPUT AND PARAMETER UNCERTAINTY ON STREAMFLOW SIMULATIONS IN LARGE UNDER-INSTRUMENTED BASINS". Diss., The University of Arizona, 2010. http://hdl.handle.net/10150/195641.
Texto completoSun, Jin. "Conquering Variability for Robust and Low Power Designs". Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145458.
Texto completovan, Wyk Hans-Werner. "A Variational Approach to Estimating Uncertain Parameters in Elliptic Systems". Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/27635.
Texto completoPh. D.
Bogodorova, Tetiana. "Modeling, Model Validation and Uncertainty Identification for Power System Analysis". Doctoral thesis, KTH, Elkraftteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-218008.
Texto completoDet är allmänt accepterat att korrekt modellering och identifiering av systemet är bland de mest viktiga utmaningarna som kraftsystemoperatörer ställs inför när de hanterar scenarior med instabiliteter och oförutsedda händelser. Det senare är vanligen hanterat med speciella beräkningsverktyg som låter operatören förutse utvecklingen och utföra lämpliga åtgärder enligt de protokoll som finns vid olika systemhändelser. För att försäkra sig om att operatörer tar de korrekta, simuleringsbaseda besluten måste kraftsystemsmodellen kontinuerligt valideras. Denna avhandling undersöker problem inom modellering, identifiering och validering av kraftsystem, formulerade och baserade på data tillhandahållet av operatörer, samt erbjuder nya metoder och fördjupade insikter i delar av en identifieringscykel som beaktar kraftsystemets. Ett av de problem som denna avhandling tar upp är val av en programmiljö för simulering och modellering som ger transparens och möjlighet till otvetydigt modellutbyte mellan systemoperatörer. Modelica är ett ekvationsbaserat programspråk som uppfyller dessa krav. I denna avhandling utvecklades enfasekvivalenter i Modelica som blev validerade mot konventionella program för simulering, såsom SPS/Simulink och PSAT i MATLAB. Parameterestimering i Modelica-modellerna kräver en modulär och utbyggbar verktygslåda. Därför har verktyget RaPiD Toolbox, som tillhandahåller systemidentifieringsalgoritmer för Modelica-modeller, utvecklats i MATLAB. Bidrag från denna avhandling är en implementation av ett partikelfilter (en sekventiell Monte Carlo-metod) och valideringsmetrik för parameteridentifiering. Prestandan i den föreslagna algoritmen har jämförts med partikelsvärmoptimering (PSO) då den är kombinerad med simplexsök och parallellisering. Partikelfiltret överträffade PSO när modellparametrar i turbinregulatorn i ett grekiskt kraftverk skulle estimeras utifrån verklig mätdata. Avhandling analyserar också olika modellstrukturer (NARX, Hammerstein-Wiener-modeller, och överföringsfunktioner med höga ordningstal) som används för att reproducera den ickelinjära dynamiken hos statiska reaktiv effekt-kompenserare (SVC) vid ofullständig information som är tillgänglig för systemoperatören National Grid. Undersökningen visar att den vanliga SVC-modellen är dålig på att reproducera den verkliga, uppmätta dynamiken. Genom att matematiskt modellera problemet som en svart låda har en identifieringsmetod föreslagits. Vidare, genom att kombinera modelleringen som en svart låda med fysikaliska principer har givit den bästa anpassningen till utdata. Metodologin för identifieringscykeln tillsammans med valet av modellkomplexitet och svårigheter med modellvalidering har utförligt presenterats. Slutligen, ett av de främsta bidragen är en ny metod för att formulera osäkerheten i parameteruppskattningarna i form av en blandning av normalfördelningar med flera typvärden som estimeras med partikelfiltrets utdata genom att använda statistiska metoder för att välja standardavvikelsen. Detta ger kraftsystemanalytiker möjlighet att utforma valideringstest för den valda modellen.
QC 20171121
EU FP7 iTesla project
Muhammad, Ruqiah. "A new dynamic model for non-viral multi-treatment gene delivery systems for bone regeneration: parameter extraction, estimation, and sensitivity". Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6996.
Texto completoSon, Kyongho. "Improving model structure and reducing parameter uncertainty in conceptual water balance models with the use of auxiliary data". University of Western Australia. School of Environmental Systems Engineering, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0094.
Texto completoJuutilainen, I. (Ilmari). "Modelling of conditional variance and uncertainty using industrial process data". Doctoral thesis, University of Oulu, 2006. http://urn.fi/urn:isbn:9514282620.
Texto completoPinkwart, Nicolas [Verfasser] y Jürgen [Akademischer Betreuer] Kähler. "Parameter Uncertainty and the Interest Rate Smoothing Behavior of the European Central Bank / Nicolas Pinkwart. Betreuer: Jürgen Kähler". Erlangen : Universitätsbibliothek der Universität Erlangen-Nürnberg, 2012. http://d-nb.info/102031382X/34.
Texto completoHaller, Vanessa. "Ecological models for threat management: Considering the unknowns using numerical analysis and machine learning". Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/210467/1/Vanessa_Haller_Thesis.pdf.
Texto completoClaußen, Arndt [Verfasser]. "Essays on risk management of financial institutions : systematic risk, cross-sectional pricing of risk factors, parameter errors affecting risk measures, and credit decisions under parameter uncertainty / Arndt Claußen". Hannover : Technische Informationsbibliothek und Universitätsbibliothek Hannover (TIB), 2015. http://d-nb.info/1078747318/34.
Texto completoSorgatz, Julia Verfasser], Holger [Akademischer Betreuer] [Schüttrumpf y Kerstin [Akademischer Betreuer] Lesny. "Towards reliability-based bank revetment design : investigation of limit states and parameter uncertainty / Julia Sorgatz ; Holger Schüttrumpf, Kerstin Lesny". Aachen : Universitätsbibliothek der RWTH Aachen, 2020. http://d-nb.info/122799298X/34.
Texto completoKouki, Slim. "An experiment on the parameter uncertainty of hydrological models with different levels of complexity in a climate change context". Doctoral thesis, Université Laval, 2016. http://hdl.handle.net/20.500.11794/26979.
Texto completoThe possibility to estimate the impact of climate change on the hydrological behavior of hydrosystems, the hydrological risks, and the associated resources is a necessity in order to anticipate the inevitable and necessary adaptations that must consider our societies. In this context, the doctoral project presents a study on the evaluation of the uncertainty of hydrological projections for the future climate when considering: (i) The non-robustness of hydrological model parameter identification, (ii) the use of several ensembles of equifinal parameter sets over a given calibration period and (iii) the use of different model structures for the hydrological model. To quantify the impact of the first source of uncertainty on the model outputs, four climatically contrasted sub-periods are first identified within the observed time series. The models are calibrated on each of these four periods, then generated outputs are analyzed on calibration and validation data. The calibration and validation tests were performed according to the configurations of four Different Split-sample Tests (Klemeš, 1986; Wilby, 2005; Seiller et al., 2012; Refsgaard et al., 2014). In order to study the second source of uncertainty related to the model structure, the equifinality of the parameter sets is taken into account by considering an ensemble of equifinal parameter sets for each sub-period calibration. Finally, to assess the third source of uncertainty, five hydrological models of different levels of complexity are applied (GR4J, MORDOR, HSAMI, SWAT, and HYDROTEL) on the watershed of the Au Saumon River (Québec, Canada).The three sources of uncertainty are assessed in the past observed period and in future climate conditions. Results show that, given the evaluation approach followed in this Ph.D. research, the use of different levels of complexity of hydrological models is the major source of variability in streamflow projections in future climate conditions for the five models tested. This is followed by the lack of robustness of parameter identification. The hydrological projections generated by an ensemble of equifinal parameter sets are close to those associated with the optimal set. Therefore, it seems that greater effort should be invested in improving the robustness of models for climate change impact studies, especially by developing more suitable model structures and proposing calibration procedures that increase their robustness. This work serves to provide a detailed response on our ability to make a diagnosis of the impacts of climate change on water resources of the Au Saumon watershed and proposes a novel methodological approach that can be directly applied or adapted to other hydro-climatic contexts.
Sorgatz, Julia [Verfasser], Holger [Akademischer Betreuer] Schüttrumpf y Kerstin [Akademischer Betreuer] Lesny. "Towards reliability-based bank revetment design : investigation of limit states and parameter uncertainty / Julia Sorgatz ; Holger Schüttrumpf, Kerstin Lesny". Aachen : Universitätsbibliothek der RWTH Aachen, 2020. http://d-nb.info/122799298X/34.
Texto completoRajaraman, Srinivasan. "Robust model-based fault diagnosis for chemical process systems". Texas A&M University, 2003. http://hdl.handle.net/1969.1/3956.
Texto completoDebchoudhury, Shantanab. "Parameter Estimation from Retarding Potential Analyzers in the Presence of Realistic Noise". Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/88466.
Texto completoDoctor of Philosophy
The plasma environment in Earth’s upper atmosphere is dynamic and diverse. Of particular interest is the ionosphere - a region of dense ionized gases that directly affects the variability in weather in space and the communication of radio wave signals across Earth. Retarding potential analyzers (RPA) are instruments that can directly measure the characteristics of this environment in flight. With the growing popularity of small satellites, these probes need to be studied in greater detail to exploit their ability to understand how ions - the positively charged particles- behave in this region. In this dissertation, we aim to understand how the RPA measurements, obtained as current-voltage relationships, are affected by electronic noise. We propose a methodology to understand the associated uncertainties in the estimated parameters through a simulation study. The results show that a statistics based algorithm can help to interpret RPA data in the presence of noise, and can make autonomous, robust and more accurate measurements compared to a traditional non-linear curve-fitting routine. The dissertation presents the challenges in analyzing RPA data that is affected by noise and proposes a new method to better interpret measurements in the ionosphere that can enable further scientific progress in the space physics community.
Abu, Rumman Malek. "Conjunctive Management of Surface Water and Groundwater Resources". Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6917.
Texto completoBushnell, Tanner Hans. "Parameter Importance of an Analytical Model for Transport in the Vadose Zone". Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1728.pdf.
Texto completoSharp, Jesse A. "Numerical methods for optimal control and parameter estimation in the life sciences". Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/230762/1/Jesse_Sharp_Thesis.pdf.
Texto completo