Sentence examples for model performance resulted from inspiring English sources
This ensured that variability in model performance resulted from pseudo-absence selection, and not by omission of important predictor variables into the model (i.e. missing explanatory variables for capturing autocorrelation, biotic, or historical influences).
This paper reports improved model performance resulting from the introduction of variable surface roughness in the operational air-quality model ADMS-Urban (v3.1).
Finally, our analyses could not account for any local variations in model performance resulting from any other factor beyond the volume of visits.
More specifically, we note that in calculating P5 and P6, the between-imputation variability in and is averaged out (and thus eliminated before assessing model performance), resulting in a single deterministic prediction, derived from observed x and y.
Variations of HYSPLIT's plume dispersion were tested against measurements of anthopogenic PM from air quality networks in San Diego County to optimize simulation time and model performance, resulting in the selection of the Gaussian-horizontal and Top-Hat vertical puff concentration distribution parameterization.
Model performances resulted extremely sensitive to band position, suggesting the importance of using hyperspectral sensors with contiguous spectral bands.
Allowing a marginal decrease in model performance results in a substantial decrease in the number of selected variables.
Even though our models were based on monthly averages, included spatiotemporal modeling in addition to GIS predictors, and were applied to a larger domain (the northeastern and midwestern United States as opposed to three small areas in Europe), our model performance results were similar.
Introducing material properties variation with film thickness into models of thermopile performance resulted in improved estimates.
The model performance has resulted to be quite promising.
Jackknifing of predictor variables showed that for 2004, per capita income was the single best variable for model performance, and resulted in the largest decrease in model performance when omitted (Figure S6).
