Sentence examples for addressing the parameter from inspiring English sources

In this paper, we borrow the notion of parameter adaptation with the objective of addressing the parameter setting dependencies mentioned above, using a strategy based on a Bayesian network.

We would like to emphasise, however, that despite these shortcomings, we have used all the available data efficiently and parameterised a full demographic model for this species for the first time, simultaneously addressing the parameter uncertainty explicitly, and have therefore improved the current understanding of Speleomantes demography significantly.

This work focuses on this issue by addressing the parameters identification problem for third-order models for synchronous generators.

Addressing the parameters outlined above requires a bipartisan effort in a country that is so deeply divided by partisanship it is unlikely to advance anytime soon.

Much of this is due to limitations in laboratory detection and translation of animal studies to human health effects, as well as insufficiently addressing the parameters of exposure in a clinical dental setting.

Several studies reported in the literature addressing the parameters identifiability in metabolic networks are exclusively concentrated in the model structure, called structural identifiability (e.g., Davidescu and Jørgensen [ 9]; Roper et al. [ 10]; Nikerel et al. [ 11]), and do not take into account the available experimental data.

This paper addresses the parameter identification of friction-type hysteretic isolators based on the versatile Bouc Wen differential model.

In this section, we use the method of maximum likelihood to address the parameter estimation and conduct a simulation to examine the performance of this method.

In this article, we address the parameter estimation of micromotion targets in synthetic aperture radar (SAR), where scattering parameters and micromotion parameters of targets are coupled resulting in a nonlinear parameter estimation problem.

The proposed method was extended to address the parameter identification for systems with topological constraints.

The parameters are classified, and subsequently the probability and interval methods are separately applied to address the parameters with sufficient and insufficient experimental samples.