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Three life prediction models were selected and compared to predict failure lifetime, in which the Ostergren model related to phase angle was modified to achieve a better predictive precision.
Several local and non-local analytical approaches were compared to predict experimental results.
Cleavage fracture toughness data is compared to predict the effects of specimen size and crack depth on fracture behavior.
Regression models including chemical composition, in vitro digestibility and near-infrared reflectance spectroscopy (NIRS) were compared to predict the energy content of several feed ingredients for poultry.
The performance of two deterministic, such as inverse distance weighting (IDW) and radial basis function (RBF) and two stochastic, i.e., ordinary kriging (OK) and universal kriging (UK) interpolation methods was compared to predict spatio-temporal variation of groundwater depth.
For building the regression models two different variable selection approaches namely, genetic function approximation (GFA) and sequential multiple linear regression (SQ-MLR) were used and compared to predict the HIV-1IN inhibition activity.
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Calculated values of thermal performances are compared to predicted values.
The measured release profile was compared to predicted Fickian models.
The measured calibration factors are compared to predicted values from calculations using a Gaussian kernel.
Then, the best obtained conditions were tested and the experimental results compared to predicted results.
The results were compared to predicted values by calculating the RSE percentages (Eq. 6).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com