Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 106 for “"Stochastic Simulation"”.
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Machine Learning and Stochastic Simulation for Inventory Management
… tolerance for different category of materials. Stochastic simulation then applies the learned predictive distributions to quantify optimal safety stock levels under uncertainties. This considers desired service levels, holding costs, risk tolerance, cost-risk tradeoffs and potential disruptions …
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Stochastic simulation of a selection experiment in maize
… models to give 24 different situations for the simulation study. The first gene action model is linear with partial dominance for all loci. For the second and third gene action models, the genotype is partitioned into subgenotypes. The second gene action model has four subgenotypes, each of …
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Handling External Events Efficiently in Gillespie's Stochastic Simulation Algorithm
Gillespie's Stochastic Simulation Algorithm (SSA) provides an elegant simulation approach for simulating models composed of coupled chemical reactions. Although this approach can be used to describe a wide variety biological, chemical, and ecological systems, often systems have external behaviors …
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Investigation of the tau-leap method for stochastic simulation
… approach takes advantage of the fact that the stochastic simulation algorithm (SSA) and the tau-leap method can be represented as a special type of counting process, that can essentially "couple", or tie together, a single realization of the SSA process to one of the tau-leap. Because the SSA …
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Analysis of air cargo transport systems using stochastic simulation
… into account the frequency of flights and the stochastic nature of shipping quantities. Key performance and cost variables were identified, and shipping data were analyzed to determine distribution parameters. A computer simulation model called CARGOSIM was developed to represent the air …
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On Efficient Algorithms for Stochastic Simulation of Biochemical Reaction Systems
… is formalized in a precise form by a model. A simulation algorithm will realize the dynamic interactions encoded in the model. The simulation can uncover biological implications and derive further predictive experiments. Several successful approaches with different levels of detail have been …
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A stochastic simulation approach for improving response in genomic selection
… In this thesis, operations research tools of simulation, optimization and</p> <p>mathematical modeling are applied to plant breeding, specifically Genomic Selection (GS).</p> <p>GS techniques allow breeders to select the best plants to make crosses by predicting, for</p> <p>example, the heights …
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Stochastic Simulation Methods for Solving Systems with Multi-State Species
Gillespie's stochastic simulation algorithm (SSA) has been a conventional method for stochastic modeling and simulation of biochemical systems. However, its population-based scheme faces the challenge from multi-state situations in many biochemical models. To tackle this problem, Morton-Firth and …
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Insights Into Mitochondrial Genetic and Morphologic Dynamics Gained by Stochastic Simulation
… data derived from literature, we have developed stochastic simulation models of mitochondrial genetic and morphologic dynamics. Hypotheses from the mitochondrial genetic dynamics model include: (1) the decay of mtDNA heteroplasmy in blood is exponential and not linear as reported in literature. …
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Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm
Stochastic effects in cellular systems are usually modeled and simulated with Gillespie's stochastic simulation algorithm (SSA), which follows the same theoretical derivation as the chemical master equation (CME), but the low efficiency of SSA limits its application to large chemical networks. To …
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A Stochastic Simulation Model of Alarm Response Strategies on a Telemetry Floor
… To better understand the problem, a simplified simulation model was created using AutoMod<sup>®</sup> to investigate the routine processes involved in responding to cardiac arrhythmia alarms on a telemetry unit as well as the sources of noise attributing to alarm fatigue. By quantifying these …
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Stochastic Simulation and System Identification of large Signal Transduction Networks in Cells
… poorly understood mechanisms and significant stochastic effects. Networks with such properties are ubiquitous in many fields of science, especially in molecular cell biology, where, for example, large signal transduction networks are formed, by which cells transfer and process information, …
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Techniques for stochastic simulation of complex electromagnetic and circuit systems with uncertainties
… set of tools and methodologies that perform fast stochastic characterization and simulation of uncertainties in electromagnetic and circuit systems. Background information on polynomial chaos and fast stochastic numerical techniques is reviewed, and discussion is offered on comparison of different …
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A Dual Metamodeling Perspective for Design and Analysis of Stochastic Simulation Experiments
… in science and engineering, the development of stochastic simulation metamodeling methodologies has gained momentum in recent years. A majority of the existing methods, such as stochastic kriging (SK), only focus on efficiently metamodeling the mean response surface implied by a stochastic …
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Modeling Farm -Level Impacts of Federal Income Tax Reforms: A Stochastic Simulation Approach
Regarding the equivalent tax revenue, overall, there is no specific income level to which crop farm would be indifferent across tax codes. The study suggests that future research should empirically explore the effects on interest rates, savings, and investments due to tax reforms at farm levels.
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Stochastic simulation of power systems with integrated renewable and utility-scale storage resources
… We report on the development of a comprehensive simulation methodology that provides the capability to quantify the impacts of integrated renewable and ESRs on the economics, reliability and emission variable effects of power systems operating in a market environment. We model the uncertainty in …
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Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features
In this thesis we study stochastic modeling and simulation methods for biochemical systems. The thesis is focused on systems with multi-state and multi-scale features and divided into two parts. In the first part, we propose new algorithms that improve existing multi-state simulation methods. We …
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Stochastic Simulation of Hourly Rainfall, Total Cloud Cover, and Solar Radiation in Canadian Stations
… biases in their outcomes, the utilization of stochastic models presents a distinct alternative for generating synthetic long time series that exhibit similar characteristics to observed data. In this research, we have introduced three distinct univariate stochastic models specifically designed …
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