Abstract Explainable Artificial Intelligence (XAI) encompasses the strategies and
methodologies used in constructing AI systems that enable end-users to comprehend and …

Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …

Sensitivity analysis is now considered a standard practice in environmental modeling.
Several open-source libraries, such as the Sensitivity Analysis Library (SALib), have been …

Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling.
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …

Various measures can be employed to decarbonise cement production, including clinker
substitution, alternative fuels, kiln improvements, and carbon capture and storage. In this …

SALib contains Python implementations of commonly used global sensitivity analysis
methods, including Sobol (Sobol'2001, Andrea Saltelli (2002), Andrea Saltelli et al.(2010)) …

The solution of several operations research problems requires the creation of a quantitative
model. Sensitivity analysis is a crucial step in the model building and result communication …

Measuring variable importance for computational models or measured data is an important
task in many applications. It has drawn our attention that the variable importance analysis …

Variance-based approaches are widely used for Global Sensitivity Analysis (GSA) of
environmental models. However, methods that consider the entire Probability Density …

Water systems planners have long recognized the need for robust solutions capable of
withstanding deviations from the conditions for which they were designed. Robustness …