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 165 for “"model calibration"”.
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Model Calibration with Machine Learning
… the application of neural networks to financial model calibration. It provides an introduction to the mathematics of basic neural networks and training algorithms. Two simplified experiments based on the Black-Scholes and constant elasticity of variance models are used to demonstrate the …
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Risk neutral measures and GARCH model calibration
Empirical studies have shown that GARCH models can be successfully used to describe option prices. Pricing such option contracts requires the risk neutral return dynamics of underlying asset. Since under the GARCH framework the market is incomplete, there is more than one risk neutral measure. In …
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Topics on option valuation and model calibration
… numerical methods for option valuation and model calibration in L´evy process and stochastic volatility models. In the first part, a numerical scheme for simulating from an analytic characteristic function is developed. Theoretically, error bounds for bias are explicitly given. Practically, …
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Stochastic Computer Model Calibration and Uncertainty Quantification
… in the field of stochastic computer model calibration and uncertainty quantification. Simulation models are widely used in studying physical systems, which are often represented by a set of mathematical equations. Inference on true physical system (unobserved or partially observed) is …
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Geomechanical Reservoir Model Calibration and Uncertainty Assessment from Microseismic Data
… to infer reservoir property distributions. To model the geothermal reservoir stimulation, a fully coupled thermo-poroelastic finite element method (FEM) model has been developed to handle the coupled process of heat transport, fluid flow, and rock deformation. To simulate the stimulation …
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Long-memory stochastic volatility model calibration using deep neural nets
Widespread use of stochastic volatility models in the financial industry is bottlenecked by the complexity and intractability they present. Since the seminal work in quantitative finance by Black et al. and Merton, the infamous Black-Scholes model has been extensively used in the industry for …
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The Bayesian validation metric : a framework for probabilistic model calibration and validation
In model development, model calibration and validation play complementary roles toward learning reliable models. In this thesis, we propose and develop the "Bayesian Validation Metric" (BVM) as a general model validation and testing tool. We show that the BVM can represent all the standard …
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Data-driven Methods in Mechanical Model Calibration and Prediction for Mesostructured Materials
… the physical behavior of the material can be modeled based on fundamental mechanics laws and simulated through finite element analysis (FEA). A major limitation in modeling is the unknown parameters in constitutive equations that describe the constituent materials; determining these parameters …
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Model Calibration and Performance Optimization Using Multiple-Point Geostatistics and Machine Learning Techniques
The overall objective of reservoir modeling is to reduce the uncertainty of production forecasts by including all available data into the model. Most importantly, the model must be able to match the historical production while preserving geological data. In this work, some new techniques are …
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Procedure for optimal D.C. parameter extraction for hot-carrier degradation model calibration and verification
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
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Event-based hydrologic model calibration using NEXRAD in a data-poor region of southern New Jersey
Proper calibration of hydrologic models requires both reliable observed stream flow and precipitation data. Southern New Jersey has a notable lack of observed precipitation data, in particular, at the event scale; therefore model calibration represents a significant challenge. From a design …
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Seasonal influent characterization, model calibration, SRT and energy usage for nitrogen removal at a full scale wastewater plant
… (version 3.1, EnviroSim Associates Ltd.) model. It was determined that denitrification during the warm season (May and July) were mostly similar to each other and different from the sampling periods data during the cold season (October and January), in terms of COD and nitrogen …
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Analysis of a Multi-Aquifer System in the Southern Coastal Plain of Virginia by Trial and Error Model Calibration to Observed Land Subsidence
… One-dimensional vertical compaction modeling is utilized to estimate the total compaction and differentiate which fine-grained confining units or aquifer interbeds are contributing most to total compaction historically and presently. Additionally, properties of the system can be …
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Off-line calibration of Dynamic Traffic Assignment models
… traffic data. Dynamic Traffic Assignment (DTA) models have also been developed for a variety of dynamic traffic management applications. Such models are designed to estimate and predict the evolution of congestion through detailed models and algorithms that capture travel demand, network supply …
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Hydrodynamic and Water Quality Simulation of Fecal Coliforms in the Lower Appomattox River, Virginia
… of computer-based hydrodynamic and water quality models were investigated. The Dynamic Estuary Model (DYNHYD5), developed by USEPA, was used to simulate hydrodynamics within the lower Appomattox River. The Water Quality Analysis Simulation Program (WASP6.1), also developed by USEPA, was employed …
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Information, insider trading and takeover announcements
… in financial markets. We want to use a math model to analyze the inside traders' behavior when there is a potential takeover in the market. The thesis starts with a math model to capture the stock price dynamics, and then it states the term structure behaviors under the model. The thesis also …
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NIR hyperspectral imaging for animal feed ingredient applications
… derivative was effective in improving calibration model performance. The NIR HSI instrument was also compared with two commercially available single-point NIR spectrometers which are typically used in the grain and feed industry. Absorbance spectra from the NIR HSI instrument were …
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Automatic calibration of an urban microclimate model under uncertainty
Simulation models play an important role in the design, analysis, and optimization of modern energy and environmental systems at building or urban scale. However, due to the extreme complexity of built environments and the sheer number of interacting parameters, it is difficult to obtain an …
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Parameter estimation of urban drainage models
… can be used to identify flood prone areas by modelling the catchment. Currently, there are several software tools available to develop urban drainage models, and to design and analyse stormwater drainage systems in urban areas. The widely used tools in Australia are SWMM, MOUSE, DRAINS and …
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Modeling of hurricane-storm surge occurrences and analysis of their financial implications
… and should adopt wind, rainfall, and storm surge models that are computationally efficient. Several wind and rainfall models in the literature can account for climate change effects and are computationally efficient. However, current models for storm surge that can account for the effects of …
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