Results 181 to 190 of about 589,193 (313)
A Systematic Review of Microsimulation Models in Cardiometabolic Disease: Model Calibration and Validation. [PDF]
Appl Health Econ Health PolicyYang D, Cao Z, Byun J, Ban JW, Kim DD.
europepmc +1 more source
Automated model calibration with parallel MCMC: Applications for a cardiovascular system model. [PDF]
Front Physiol, 2022 Argus F +4 more
europepmc +1 more source
Calibration in a Bayesian modelling framework
, 2004 Bayesian statistics may constitute the core of a consistent and comprehensive framework for the statistical aspects of modelling complex processes that involve many parameters whose values are derived from many sources. Bayesian statistics holds great promises for model calibration, provides the perfect starting point for uncertainty analysis and ...
Jansen, M.J.W., Hagenaars, T.H.J.
openaire +2 more sources
Influence of Test Temperature and Test Frequency on Fatigue Life of Aluminum Alloy EN AW‐2618A
Advanced Engineering Materials, EarlyView.The influence of test temperature and test frequency on the fatigue life of EN AW‐2618A is investigated. High‐cycle fatigue tests are performed at different test temperatures and frequencies on the 1000 h/230°C overaged state. Both test parameters reduce fatigue life due to time‐dependent damage mechanisms.
Ying Han +5 more
wiley +1 more source
Self-Calibration in Differential Drive Dynamics/Kinematics Model [PDF]
Localization and path planning is an essential elements of mobile robots but it relies on model availability. It is difficult to obtain robot dynamics/kinematics model due to lot of constants and variables.
Ekmanis, Mārtiņš
core
Leaf gas exchange measurement for steady-state stomatal conductance model calibration. [PDF]
New PhytolRizzo KT, Lei T, Buckley TN, Bailey BN.
europepmc +1 more source
Addressing Deep Learning Model Calibration Using Evidential Neural Networks And Uncertainty-Aware Training. [PDF]
Proc IEEE Int Symp Biomed Imaging, 2023 Dawood T +4 more
europepmc +1 more source
Advanced Engineering Materials, EarlyView.Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova +2 more
wiley +1 more source
Epidemiological model calibration via graybox Bayesian optimization. [PDF]
Infect Dis ModelNiu P, Yoon BJ, Qian X.
europepmc +1 more source