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Full-Text Articles in Engineering
Parameter Estimation In Heat Transfer And Elasticity Using Trained Pod-Rbf Network Inverse Methods, Craig Rogers
Parameter Estimation In Heat Transfer And Elasticity Using Trained Pod-Rbf Network Inverse Methods, Craig Rogers
Electronic Theses and Dissertations
In applied mechanics it is always necessary to understand the fundamental properties of a system in order to generate an accurate numerical model or to predict future operating conditions. These fundamental properties include, but are not limited to, the material parameters of a specimen, the boundary conditions inside of a system, or essential dimensional characteristics that define the system or body. However in certain instances there may be little to no knowledge about the systems conditions or properties; as a result the problem cannot be modeled accurately using standard numerical methods. Consequently, it is critical to define an approach that …
Parameter Estimation Using Sensor Fusion And Model Updating, Kevin Francoforte
Parameter Estimation Using Sensor Fusion And Model Updating, Kevin Francoforte
Electronic Theses and Dissertations
Engineers and infrastructure owners have to manage an aging civil infrastructure in the US. Engineers have the opportunity to analyze structures using finite element models (FEM), and often base their engineering decisions on the outcome of the results. Ultimately, the success of these decisions is directly related to the accuracy of the finite element model in representing the real-life structure. Improper assumptions in the model such as member properties or connections, can lead to inaccurate results. A major source of modeling error in many finite element models of existing structures is due to improper representation of the boundary conditions. In …
Parameter Estimation In Linear Regression, Kati Ollikainen
Parameter Estimation In Linear Regression, Kati Ollikainen
Electronic Theses and Dissertations
Today increasing amounts of data are available for analysis purposes and often times for resource allocation. One method for analysis is linear regression which utilizes the least squares estimation technique to estimate a model's parameters. This research investigated, from a user's perspective, the ability of linear regression to estimate the parameters' confidence intervals at the usual 95% level for medium sized data sets. A controlled environment using simulation with known data characteristics (clean data, bias and or multicollinearity present) was used to show underlying problems exist with confidence intervals not including the true parameter (even though the variable was selected). …