Sentence examples for model outputs using from inspiring English sources

In this study, a general framework for analytical UQ of model outputs using a Gaussian process (GP) metamodel is presented, where case inputs are characterized as normal and/or uniform random variables.

The model calibration process refers to an estimate of the model parameters to fit the model results to a set of observed data, while the validation process refers to an evaluation of the results of the model outputs using the calibrated model parameters compared to the observed outcomes.

The AMIGO_LRank method ranks the model parameters according to their influence on the model outputs, using several sensitivity measures.

The model discrepancy quantifies the ability of the simulator to reproduce the physical state of the system being modelled when the physical inputs are used, and is estimated by examination of model outputs using a variety of model inputs.

Though global functional relationships are strikingly similar between the two models, the normalized-Hill model outputs using all default parameters contains damped oscillations that are not prominent in the biochemical model (compare Figure 4A with the left panel in Figure 7).

Spatial model outputs using observed presence and absence data for Aedes albopictus, an invasive species in (Southern) Europe, obtained through an international network of scientific collaborators, are then compared to potential distribution maps computed using a multicriteria decision analysis approach (MCDA) based on expert knowledge.

The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation.

The deterministic model simulation outputs using the parameters predicted by each algorithm are provided as supplementary material.

The probability p y|x,θ) for a given tag sequence y can be computed from the model output using a softmax operation: p y|x, theta) = frac{e^{s x, y)}} {sum_{j} e^{s x, j)}}.

Due to the spatially detailed mapping of isoprene emissions over the study area, it was possible to validate the model output using field data collected at a precise time and place by replicating those conditions in the model.

We analyzed the model output using the R statistical programming language, and created the graphs using the R package ggplot2 (31).