Being Sensitive to Uncertainty
University of Wisconsin–Whitewater · Los Alamos National Laboratory
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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
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961
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- FWCI
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Authors
2Topics & keywords
Keywords
- Sensitivity (control systems)
- Computer science
- Uncertainty quantification
- Uncertainty analysis
- Measurement uncertainty
- Propagation of uncertainty
- Data mining
- Algorithm
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