Criteria weights determined from pairwise comparisons are often the greatest contributor to
the uncertainties in the AHP-based multi-criteria decision making (MCDM). During an …

In this paper, the potential benefits of quasi-Monte Carlo (QMC) methods for uncertainty
propagation are assessed via two applications: a numerical case study and a realistic and …

DNA cleavage by nanomaterials has the potential to be utilized as an innovative tool for
gene editing. Numerous nanomaterials exhibiting DNA cleavage properties have been …

Sensitivity analysis is important for determining the parameters in the model calibration
process. In our study, a variance-based global sensitivity analysis (extended Fourier …

In risk assessment, the moment‐independent sensitivity analysis (SA) technique for
reducing the model uncertainty has attracted a great deal of attention from analysts and …

Sensitivity analysis, calibration, and verification of crop model parameters improve crop
model efficiency and accuracy, facilitating its application. This study selected five sites within …

Uncertainty quantification and global sensitivity analysis are indispensable for patient‐
specific applications of models that enhance diagnosis or aid decision‐making. Variance …

A special computational technology for sensitivity analysis of ozone concentrations
according to variations of rates of chemical reactions is developed. It allows us to study a …

The aim of our research was to develop a dairy farm technology planning system which
models the material flow and value chain of a sample dairy farm. By this model, widespread …

A 3‐stage sensitivity analysis approach, based on analysis of variances technique for
calculating Sobol's global sensitivity indices and computationaly efficient Monte Carlo …