BACKGROUND Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relati...

uncertainty plays a major role in any project evaluation and management process. one of the trickiest parts of any production project work is its cost and time forecasting. since in the initial phases of production projects uncertainty is at its highest level, a reliable method of project scheduling and cash flow generation is vital to help the managers reach successful implementation of the pr...

Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are rarely confronted. This pa...

Data quality and uncertainty modeling for spatial data and spatial analyses is regarded as one of the disciplines of geographic information science together with space and time in geography, as well as spatial analysis. In the past two decades, a lot of research efforts have been devoted to uncertainty modeling for spatial data and analyses, and this paper presents our work in this research are...

Proper characterization of uncertainty is a challenging task. Depending on the sources of uncertainty, various uncertainty modeling frameworks have been proposed and studied in the uncertainty quantification literature. This paper applies various uncertainty modeling frameworks, namely possibility theory, Dempster-Shafer theory and probability theory to isosurface extraction from uncertain scal...

When there are many people who don't need to expect something more than the benefits to take, we will suggest you to have willing to reach all benefits. Be sure and surely do to take this uncertainty theory a branch of mathematics for modeling human uncertainty that gives the best reasons to read. When you really need to get the reason why, this uncertainty theory a branch of mathematics for mo...

this paper proposes a family of robust counterpart for uncertain linear programs (lp) which is obtained for a general definition of the uncertainty region. the relationship between uncertainty sets using norm bod-ies and their corresponding robust counterparts defined by dual norms is presented. those properties lead us to characterize primal and dual robust counterparts. the researchers show t...