Sentence examples for improved model parameters from inspiring English sources

The aim of this work is to present revised and improved model parameters for group-contribution+ (GC+) models (combined group-contribution (GC) method and atom connectivity index (CI) method) employed for the estimation of pure component properties, together with covariance matrices to quantify uncertainties in the estimated property values.

The utility of the proposed framework is illustrated for assessment of future droughts through estimation of improved model parameters of the standard precipitation index (SPI).

Recently the microscopic calculation of weak interaction mediated rates on key isotopes of iron was introduced using the proton neutron quasiparticle random phase approximation (pn-QRPA) theory with improved model parameters.

A model including individual-level predictors (gender, age, material situation, education, and preferred social distance) provided a relatively good fit to the data, but adding country-level predictors (Human Development Index, population density, and average temperature) did not improve model parameters.

The outcomes of this study pointed out the importance of spatially distributed hydrological water quality observations for improving model parameter identification and provided guidelines for choice of adequate calibration strategy and design of hydrological water quality monitoring campaign.

Here our models in [2] are elaborated upon and extended with the aim to improve model parameter estimates.

Additionally, the two approaches can be implemented simultaneously, which further improved model residuals and parameter errors, demonstrating the modularity of each approach and that both approach ill-posed problems in a distinct manner.

Random intercepts can account for unbalanced data, correlation among observations, and provide improved model fit and parameter estimation [39] (but see [11]).

To assess whether suggested parameter changes improved model performance we compared a model with modified parameters to a model with the original parameter set, but otherwise in the exact same conditions.

The third model was the improved model shown in Table 2 with parameters trained by the MINC and FOD datasets, abbreviated as IAMF.

Potential improvements include further investigating historical eruption accounts and geological data at Santorini and analogous volcanoes to improve model input parameters such as grain size distributions, column height estimates or characterisation of eruption time-series as a Poisson point process.