40 citations · 48 across the 6 of their papers we have counts for
6 papers
Recent advances in Meta-model of Optimal Prognosis
Thomas Most, Johannes Will
In real case applications within the virtual prototyping process, it is not always possible to reduce the complexity of the physical models and to obtain numerical models which can…
Estimation of material parameter uncertainties using probabilistic and interval approaches
Thomas Most
Within the calibration of material models, often the numerical results of a simulation model are compared with the experimental measurements . Usually, the differences bet…
Efficient variance-based reliability sensitivity analysis for Monte Carlo methods
Thomas Most
In this paper, a Monte Carlo based approach for the quantification of the importance of the scattering input parameters with respect to the failure probability is presented. Using…
A global optimization approach for antenna design using analytical derivatives from high-frequency simulations
Thomas Most, Peter Krenz, Ralf Lampert
Antennas are more prevalent than ever enabling 5G connectivity for wide ranging applications like cellular communication, IoT, autonomous vehicles, etc. Optimizing an antenna desig…
Sensitivity analysis using the Metamodel of Optimal Prognosis
Thomas Most, Johannes Will
In real case applications within the virtual prototyping process, it is not always possible to reduce the complexity of the physical models and to obtain numerical models which can…
Robustness investigation of cross-validation based quality measures for model assessment
Thomas Most, Lars Gräning, Sebastian Wolff
In this paper the accuracy and robustness of quality measures for the assessment of machine learning models are investigated. The prediction quality of a machine learning model is…