The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of ideas from mathematics, statistics and engineering being used to lend credence to predictive assessments of risk but also to design actions (by engineers, scientists and investors) that are consistent with risk aversion. The objective of this Handbook is to facilitate the dissemination of the forefront of UQ ideas to their audiences. We recognize that these audiences are varied, with interests ranging from theory to application, and from research to development and even execution.
Shares cutting edge Uncertainty Quantification ideas with a wide audience
Overviews fundamental challenges, applications, and emerging results
Draws together the work of mathematicians, statisticians, and engineers
Opens the work of top international researchers through an accessible reference work
Includes supplementary material: sn.pub/extras
Roger Ghanem
Polynomial Chaos Risk Analysis Risk Models Sensitivity Analysis Uncertainty Quantification
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