articleComputing in Science & EngineeringMar 1, 2007Closed access

Being Sensitive to Uncertainty

University of Wisconsin–Whitewater · Los Alamos National Laboratory

Indexed incrossref

Abstract

Predictive modeling's effectiveness is hindered by inherent uncertainties in the input parameters. Sensitivity and uncertainty analysis quantify these uncertainties and identify the relationships between input and output variations, leading to the construction of a more accurate model. This survey introduces the application, implementation, and underlying principles of sensitivity and uncertainty quantification

Citation impact

961
total citations
FWCI
21.07
Percentile
100%
References
16
Citations per year

Authors

2

Topics & keywords

Keywords
  • Sensitivity (control systems)
  • Computer science
  • Uncertainty quantification
  • Uncertainty analysis
  • Measurement uncertainty
  • Propagation of uncertainty
  • Data mining
  • Algorithm
No related works found for this paper.

Funding